The Effects of Language Background on Musical Melody and Rhythm Perception

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The Effects of Language Background on Musical Melody and Rhythm Perception Melis Çetinçelik

Student ID: 11353635 Number of EC: 26 EC

Time period: 06.02.2017- 30.07.2017 Supervisor: Dr. Makiko Sadakata

Co-assessor: Dr. Paula Roncaglia-Denissen

Music Cognition Group, Institute for Logic, Language, and Computation MSc in Brain and Cognitive Sciences, University of Amsterdam

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Abstract

This study investigates whether learning a second language enhances musical rhythmic and melodic perception, with a particular focus on the rhythmic and melodic differences between different languages. We tested Turkish, Mandarin, and Dutch L2 speakers of English, and

Turkish monolinguals, on their rhythmic and melodic musical perception. To control for potential individual and cultural differences, participants’ phonological and working memory skills, as well as their years of musical training and daily exposure to music were assessed. Our findings suggest that mastering a second language enhances musical rhythmic and melodic perception, but only when the acquired second language is rhythmically or melodically different than the

individual’s native language. Rhythmic aptitude scores of speakers of two rhythmically different languages (Turkish-English, and Mandarin-English) were significantly higher than those of speakers of rhythmically similar languages (Dutch-English). A similar pattern was observed for melody perception, with significantly higher melodic aptitude results of only those participants who spoke a tonal language (Mandarin-English). Our results point at a domain-general cognitive transfer of melodic and rhythmic perception between the language and music domains.

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Language and music are two human universals, two high-level cognitive functions which require complex cognitive and motor processes (Arbib, 2013). Both language and music are built upon acoustic signals, which require the listener to attend to, anticipate, and quickly interpret the sound segments. Due to the similarities in the way music and speech are perceived, the

relationship between language and music has been a topic of interest for numerous researchers from various disciplines, such as linguistics (Jackendoff, 2009), musicology, and neuroscience (Besson & Schön, 2001; Patel & Peretz, 1997). Two main points of interest are the perception of rhythmic and pitch information, as both rhythm and pitch play a fundamental role in both

domains by aiding the listener in the seemingly complex task of music and speech perception. In both music and language, making sense of the sound stream relies heavily on

perceptual grouping, which is the mental clustering of acoustic events into meaningful units, such as words and sentences in language, and phrases in music (Patel, 2006). Musical rhythm is a fundamental aspect of music, and is composed of a number of elements such as the grouping of tones into phrases, an underlying beat, and the organization of the periodicity to create the musical meter (Patel, 2003a).

Similar to musical rhythm, linguistic rhythm marks how speech is organized in time by grouping the sound stream into meaningful units such as words and sentences. As with musical rhythm, linguistic rhythm is composed of several elements which influence its organization: the pattern of grouping words within utterances and pausing in between, the durational pattering of the syllables, and the pattern of stressed and unstressed syllables (Patel, 2003a). This leads to a classification of world languages into three broad groups: stress-timed, syllable-timed, and mora-timed. Stress-timed languages, such as English, Dutch, and Mandarin, use the metric foot to organize speech (Pike, 1945). This means that the duration between the stressed syllables are fairly constant, and the unstressed syllables are compressed to fit into the time interval (Hayes,

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1985). On the other hand, syllable-timed languages, such as Turkish and French, use syllable as the speech organization unit, regardless of the stress assignment of the syllable. As every syllable takes up approximately the same amount of time in speech, syllable-timed languages are

generally perceived as more monotonic compared to stress-timed languages, and the way they sound has been even likened to the sound of a machine gun (James, 1940; Nespor, Shukla, Mehler, 2011). Finally, a third group termed mora-timed languages (e.g. Japanese) uses mora as its organization unit. The focus of this study is on stress- and syllable-timed languages. However, the key point is that there are crucial rhythmic differences between the different classes, which are apparently significant enough to be perceived even by newborns. Nazzi and colleagues (1998) noted that French newborns could discriminate between English (stress-timed) and Japanese (mora-timed), but not between English and Dutch, two stress-timed languages. Similar findings were obtained for adults, who successfully discriminated between English and Spanish (syllable-timed), but not between English and Dutch (Ramus, Dupoux, & Mehler, 2003). Taken together, the findings suggest that speech rhythm carries important prosodic information, which is salient at the perceptual level.

Pitch is another fundamental attribute of both music and language. Musical pitch constitutes the basis of musical structure, along with rhythmic information (McDermott & Hauser, 2005). In music, pitch can signify the composition, or can be used to express different affective states (Alexander, Bradlow, Ashley, & Wong, 2008). In language, the roles of pitch and melodic variation differ across languages. In tonal languages such as Mandarin and Cantonese Chinese, pitch variations convey lexical information. For instance, in Mandarin Chinese, the syllable /ma/ can bear four different meanings depending on the lexical tone it was produced with: when uttered with the high-level tone 1 it means “mother,” “hemp” when with the rising tone 2, “horse” with the dipping tone 3, and “scold” with the falling tone 4. In non-tonal

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languages, on the other hand, variations in pitch do not add to or change the meaning of the utterance. Rather, variations are used to convey pragmatic meaning through prosody and intonation, in order to emphasize a particular element in a sentence, or to reflect the emotional state of the speaker (e.g. low pitch speech might indicate that the speaker is unhappy; Alexander et al., 2008).

The tone element in speech is integral to tonal languages since failing to pronounce a syllable with the accurate tone might hinder communication. Although prosody is by no means a feature that can be overlooked as it carries important additional information that might not be conveyed by grammar only, it is less related to major communicative failures in which the

meanings of words are understood inaccurately, but rather likely to result in failures to perceiving the correct affective state of the speaker (Monetta, Cheang, & Pell, 2008).

As can be inferred, tonal language speakers have to master the lexical tones and their phonological representations to be able to fully comprehend and speak the language. This sensitivity in detecting tones might not be readily available in non-tonal language speakers since their languages do not lay this ability as an integral condition to excel in the respective language. Indeed, a study by Halle, Chang and Best (2004) demonstrated that when compared to tonal language (Mandarin) speakers, non-tonal (French) language speakers showed less sensitivity to tone contour differences. Nevertheless, French speakers still showed substantial sensitivity to the contour differences, indicating that they do sense the tone contour differences, but simply do not place the tones in linguistic categories (Halle, Chang, & Best, 2004). However, non-tonal

language speakers might not be that sensitive to subtle, prosody-bearing tone changes in speech since their native languages do not explicitly require them to attend to the subtle pitch variations to master their native tongue. As a result, they might have developed less sensitivity to pitch

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variations in speech, which might be reflected in the ways they perceive pitch differences in music, as well.

It has been a longstanding debate in cognitive science whether language and music are processed and governed by domain-specific cognitive mechanisms (e.g. Peretz & Zatorre, 2005), or whether they are controlled by overarching domain-general mechanisms (e.g. Patel, 1998; 2003b). Comparisons of rhythmic and pitch information in language and music provide an interesting arena to test these hypotheses as they form the basis of language and music, being the most salient components that span over both domains. Until now, research has presented a mixed picture with regards to domain-specificity for both components.

To investigate the critical issue of cross-domain effects between language and music, Roncaglia-Denissen and colleagues (2013) compared German L2 speakers of English and Turkish L2 speakers of German in a musical rhythmic aptitude task. They found that Turkish L2 speakers of German performed significantly better, a finding which may be explained by the Turkish-German speakers’ exposure to different linguistic rhythmic features as a result of their language experience. Mastering two languages with different rhythmic properties (e.g. Turkish and German; Turkish being a syllable-timed and German a stress-timed language) may enhance the speakers’ sensitivity to general acoustic properties in both the language and the musical domain, as demonstrated by the results of the previous study by Roncaglia-Denissen et al. (2013). Hence, Turkish-German bilinguals might have become more sensitive to rhythmic cues compared to monolinguals, which enables them to perform better in tasks of musical rhythm aptitude

compared to bilinguals of two rhythm-wise similar languages (such as English and German or Dutch).

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Roncaglia-Denissen, Roor, Chen, and Sadakata (2016) further investigated whether being competent in a second language, regardless of the rhythmic differences between the two

languages, results in an enhancement of musical rhythmic perception. Although all groups of bilinguals (Turkish, Dutch, Mandarin L2 speakers of English) performed better than Turkish monolinguals on musical aptitude tasks, the performance of Turkish-English bilinguals were significantly better than Dutch-English bilinguals, suggesting that mastering a second language whose rhythmic properties differ from one’s native tongue results in an even greater

enhancement. As the rhythmic differences between the two languages become greater, the individuals’ attention and sensitivity to rhythmic and acoustic variations becomes also more enhanced, resulting in an improved rhythmic recognition ability.

In light of these previous findings, the aim of the current study is to determine whether there is an effect of the linguistic background on the individuals’ rhythmic and melodic perceptual abilities. Based on earlier research suggesting that mastering two languages with different rhythmic properties such as Turkish and German may enhance the speakers’ sensitivity to general acoustic properties in the musical domain (Roncaglia-Denissen et al., 2013), we tested second language (L2) learners of English with different native languages. The different native language- English language pairs were selected purposefully to allow for a comparison between languages with different rhythmic and melodic structures, thereby extending the previous research. To this end, we tested one group of Turkish monolinguals and three groups (Dutch, Mandarin and Turkish) of L2 learners of English. With regards to their rhythmic structures, English and Dutch are both stress-timed languages, whereas Mandarin and Turkish are syllable-timed. Therefore, Turkish and Mandarin L2 learners of English are expected to have been exposed to the rhythmic differences among their first and second languages in the course of learning English, as using the rhythmic information in the language is an integral element in

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successfully acquiring a language (Goetry & Kolinsky, 2000). Thus, in order to be proficient in English, they need to attend to, and encode different sets of rhythmic information in the two languages. Dutch L2 learners of English, on the other hand, are not trained to detecting

differences in rhythmic structure between their native and second languages as Dutch and English share the same rhythmic patterns. As a result, Turkish and Mandarin speakers of English might be better than Dutch-English speakers in discriminating rhythmic variation not only in language, but also in music, indicating a cross-domain effect (Roncaglia-Denissen et al., 2016).

The groups selected for the current study also allow for a comparison with regards to melodic perception. Although Roncaglia-Denissen et al. (2016) demonstrated initial findings on melodic perception, they did not portray a full picture of musical melody aptitude across groups, taking possible confounding factors into account. As discussed in detail above, tonal language speakers are better at detecting melody variations compared to non-tonal language speakers (Alexander et al., 2008). In line with previous findings, we expect that Mandarin speakers would have enhanced accuracy in musical pitch processing, as measured by the melody subset of the MET. However, although previous research suggests an advantage of speaking a (second) tonal language in pitch perception, no one to the best of our knowledge has studied whether mastering a second non-tonal language brings about a similar enhancement in musical pitch perception. We aim to fill this gap by testing bilinguals of different language pairs (Dutch, Turkish, and

Mandarin L2 speakers of English), which would allow for a comparison of tonal and non-tonal language pairs.

In line with Roncaglia-Denissen et al. (2013), we expect that mastering two languages with different rhythmic properties would enhance musical rhythm perception. However, it is a question whether, with careful analyses taking possible confounding factors into account, all bilingual groups, regardless of the rhythmic differences between the languages, would have

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enhanced rhythmic aptitude, as shown by Roncaglia-Denissen et al. (2016). Therefore, one of the aims of the current study is to replicate the Roncaglia-Denissen et al. (2016) study with respect to rhythmic aptitude. We expect to demonstrate an additional effect of learning a second language with a speech rhythm different than English, such as Turkish or Mandarin, as it is more

demanding and possibly acoustically enhancing, than speaking two languages with the same set of rhythmic properties.

With regards to melodic abilities, we expect to see an effect of speaking a tonal language on pitch perception, in line with previous findings (Alexander et al., 2008). We further aim to understand whether speaking two non-tonal languages would enhance pitch perception. If

speakers of two non-tonal languages score similarly to Mandarin-English speakers in the melodic aptitude tests, it might be suggested that the subtle intonation pattern differences between

languages might contribute to the enhancement of acoustical pitch perception as well. Materials and Methods

Participants

Participants in this study were sixty volunteer university students or recent graduates, divided into four experimental groups: 15 Mandarin L2 learners of English (8 females, Mage =

25.06 years, SD =1.98, mean age of L2 first exposure, AoL2FE = 9.93 years, SD = 2.31), 15 Turkish L2 learners of English (8 females, Mage = 23.87 years, SD = 0.92, MAoL2FE = 6.27 years,

SD = 3.283), 15 Dutch L2 learners of English (8 females, Mage = 25.53 years, SD = 4.64, MAoL2FE

= 8.80 years, SD = 3.27) and 15 Turkish monolinguals (8 females, Mage = 18.93 years, SD =

1.94).

The participants in this study allow for a comparison of different language groups, with regards to both rhythmic and pitch features. The four groups represent the following categories:

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1. Monolinguals: Turkish monolinguals

2. Bilinguals of rhythmically similar languages a. Dutch-English bilinguals

3. Bilinguals of rhythmically different languages a. Turkish-English bilinguals

b. Mandarin-English bilinguals

Based on pitch features:

1. Monolinguals: Turkish monolinguals

2. Bilinguals of melodically different languages

a. Mandarin-English bilinguals (a tonal and a non-tonal language) 3. Bilinguals of melodically similar languages

a. Dutch-English bilinguals (two non-tonal languages) b. Turkish-English bilinguals (two non-tonal languages)

All participants reported having no to little formal musical training (M = 1.53 years, SD = 1.76), without group differences in the amount of formal musical training received. None of the participants had any neurological, hearing, or visual impairment, and had normal or corrected-to-normal vision. This study was approved by the ethics committees of the Faculty of Humanities of the University of Amsterdam, Utrecht University and the Middle East Technical University, in Ankara. All participants gave their written informed consent for data collection, use and publication.

Materials

Phonological and working memory measures. Participants’ phonological memory, which is the memory for the storage and retrieval of novel sounds (Baddeley, Gathercole, &

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Papagno, 1998), was assessed using the Mottier test (Mottier, 1951). Mottier test is a non-word repetition task, consisting of six blocks. The first block of non-words consists of two syllables, and with each block, the number of the syllables are increased by one. All non-words consisted of the constant syllabic structure of one consonant followed by one vowel. For each group of

participants, the stimulus material was spoken by a native speaker of the respective language (for instance, a Turkish native speaker’s reading out the stimuli was recorded and used for the Turkish participants), and followed the phonetic rules of that language (see Appendix A for the

instructions and answer sheet).

Participants’ working memory was measured using the backward digit span task (BDS), which requires the storage and transformation of information in working memory (Oberauer et al., 2000). The version of the test used in this experiment consisted of 14 sets of two trials, which started with two numbers, increasing by one with each set. The stimulus material was spoken by a native speaker for each group, in the native language of the respective group (refer to Appendix B for the instructions and the answer sheet).

Melodic and Rhythmic Aptitude. Following Roncaglia-Denissen et al. (2016), the melodic and rhythmic subsets of the Musical Ear Test (MET; Wallentin et al., 2010) was used to measure participants’ melodic and rhythmic aptitude. The melodic aptitude subset comprised 52 pairs of melodic phrases, presenting 3-8 tones. The melodies had the duration of one measure, and were played at 100 bpm. 26 pairs of phrases contained a violation of pitch, and 13 of those 26 pairs contained a violation in the pitch contour as well. Twenty-five trials were constituted by non-diatonic tones, 20 were in the major keys and seven in minor keys.

The rhythmic aptitude subset of the MET (Wallentin et al., 2010) consisted of 52 pairs of rhythmic phrases. Rhythmic phrases were recorded using wooden blocks, and were 4 to 11 pairs long. All rhythmic phrases had the duration of one measure, and were played at 100 bpm. The

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phrases were either identical or different from each other, and the difference in the different phrases was only one beat. Rhythmic complexity was achieved by including even beat

subdivisions in 31 trials and triplets in the remaining 21 trials. Thirty-seven trials began on the downbeat and the remaining 15 trials started after it (refer to Appendix C for the instructions).

Lexical tone discrimination. The lexical tone discrimination test used by Chen, Liu and Kager (2016) was used for this study (see Appendix D for the instructions of the lexical tone test). In the test created by Chen et al. (2016), a female native speaker of Mandarin Chinese recorded segments of monosyllables /ba/, /bwɔ/, /bi/, /da/, /dwɔ/, /di/, /la/, /lwɔ/, /li/, /ma/, /mwɔ/, /mi/, /na/, /nwɔ/, /ni/, each with all four possible tones. The discrimination task consisted of two parts. In the monosyllabic part, the participants were asked to discriminate between task between different tones, i.e. between T2 and T3 and between T1 and T4. For each tonal pair, all the possible four combinations, T2–T2, T2–T3, T3–T2, and T3–T3 were presented randomly, with equal chance of each. The monosyllabic part consisted of 120 trials. In the disyllabic part, sound segments of two syllables were presented. The participants were asked to discriminate between tones T3T3–T2T3, T3T3–T3T2, T3T3–T2T2, T4T4– T1T4, T4T4–T4T1, and T4T4–T1T1. This part had a total of 180 trials (for a detailed description of the stimuli and tonal pairs, please refer to Chen et al., 2016).

Self-Reported Language Skills and History Questionnaire. To assess participants’ skills in their native and second languages, a self-reported language and history questionnaire was used. Self-reports have been shown to be a reliable measure of language skills as they are highly correlated with objective measures of language skills (Marian, Blumenfeld, &

Kaushanskaya, 2007). Participants’ command of second language were measured using the same language skills and history questionnaire used by Roncaglia-Denissen et al. (2013; see Appendix E for the questionnaires). Participants’ comprehension, reading, writing, and speaking skills in

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their native and second languages were assessed. They were also asked about their age of L2 acquisition, situations in which they acquired their L2, and the current use of and exposure to L2.

Music Background Questionnaire. Participants were given a music background questionnaire in which they were asked about their formal musical training (in years) and daily exposure to music (in hours), together with the nature of the formal musical training they have received (refer to Appendix E). Formal musical training was assessed with the number of years participants attended music lessons to learn to play an instrument and/or to sing.

Procedures

All participants were tested individually in a quiet room with a computer. Mandarin L2 learners of English were tested in Utrecht, Tilburg and in Amsterdam. Turkish L2 learners of English were tested in Amsterdam, Tilburg, Nijmegen and in Istanbul. Dutch L2 learners of English were tested in Amsterdam, and Turkish monolinguals were tested in Ankara. The order of the

administration of the tests were randomized across all participants, and each session lasted about an hour. For the rhythmic and melodic aptitude tests, and the lexical tone discrimination test, participants completed two practice trials before beginning with the actual experiment. At the end of each session, participants were given the self-reported language background and music

background questionnaire, followed by a debriefing session.

Mottier test. The Mottier rest required participants to listen to the non-words from a computer and repeat each word as accurately as possible after hearing it. Participants’ responses were recorded by the experimenter. The test was terminated when the participant failed to recall a minimum of four items in the same set. Participants’ scores were calculated on basis of the total number of correctly recalled words, with a maximum score of 30.

Backward Digit Span. Participants listened to sequences of digits from a computer, and were asked to repeat the number sequence in the reverse order they had heard. The test was

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terminated when the participant failed to correctly recall two trials. Participants’ scored were based on the total number of correctly recalled trials, with a maximum score of 14.

MET melodic aptitude test. Participants were presented with the stimulus melody segments via the computer. The test required the participants to listen to the two segments and indicate whether the two phrases were identical or different. All groups except for the Mandarin L2 learners of English performed the test using the computer. Mandarin L2 learners of English were given an answer sheet to mark their answers, while the remaining participants responded by clicking the “same” or “different” key.

MET rhythmic aptitude test. Similar to the melodic aptitude subset of the MET, participants were presented with the stimuli via the computer. They were instructed to listen to rhythmic pairs and decide whether the rhythmic phrases were identical or not. As with the melodic aptitude subset, Mandarin L2 learners of English used an answer sheet to indicate their answers, while the remaining participants responded by clicking the “same” or “different” key on the computer.

Lexical tone discrimination. Participants were presented with the lexical tone stimuli via the computer. Within this task, the presentation of disyllabic tones always preceded the

monosyllabic tones in order to prevent learning effects, as pilot tests showed that even non-tonal language (Dutch) speakers were significantly accurate in detecting monosyllabic tones (Chen et al., 2016). In both the disyllabic and monosyllabic subsets, participants were asked to

discriminate between two sound segments as fast and accurately as possible by pressing the button of their choice, labelled “same” or “different”. In order to increase the difficulty of the experiment, participants were given a time frame of one second to respond. If the participant failed to give a response within the time limit, the respective trial was considered as an incorrect response.

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Statistical Analysis

Language skills requiring the explicit (speaking and comprehension) and implicit (reading) use of rhythm and melody were regarded as possible covariates, thus, the remaining scores were disregarded for the purposes of statistical analysis in the current study. Three separate Kruskal-Wallis tests were conducted to compare the three L2-speaker groups speaking, comprehension, and reading skills, using the language skills as dependent variables, and group (Turkish, Mandarin, Dutch) as a between-subjects factor. Two additional Kruskal-Wallis tests were computed to compare participants’ daily exposure to music (assessed in number of hours per day) and years of formal musical training. As no significant differences were found regarding the two variables, these were no longer taken into account in the remaining statistical analyses.

Two analyses of variance (ANOVAs) were conducted using participants’ mean scores in the two cognitive tests (Mottier and Backward digit span) as dependent variables, and group as a between-subjects factor. To compare participants’ performances in the melody and rhythmic aptitude tests, two separate analysis of covariance (ANCOVAs) were computed, using mean scores in the respective tests as the dependent variable, group as a between-subjects factor, and participants’ scores in each cognitive test (Mottier and BDS), and their scores in the other subset of the MET as covariates. Additionally, in order to assess participants’ performances in the disyllabic and monosyllabic lexical tone discrimination tests, two ANOVAs were conducted using the mean accuracy rates as dependent variables, and group as a between-subjects factor.

Results L2 (English) Skills

No statistically significant differences were found among the three L2 speakers of English groups’ (Turkish, Mandarin, and Dutch L2-speakers of English) L2 speaking skills, p > 0.1. Significant group differences were found for participants L2 comprehension (χ2(2) = 6.18, p =

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0.04), and reading (χ2(2) = 7.77, p = 0.02) skills. Pairwise comparisons of the group mean scores for L2 reading skills revealed significant differences between the Turkish-English (M = 78.70%, SD = 13.02%) and Dutch-English (M = 91.30%, SD = 9.90%) bilingual groups. A significant group difference was also found between Turkish-English (M = 81.30%, SD = 15.98%) and Dutch-English (M = 91.30%, SD = 10.60%) groups’ L2 comprehension skills. Similarly, a significant difference was observed between the Dutch-English and Mandarin-English (M = 80.70%, SD = 11.00%) groups’ L2 comprehension skills. Participants’ self-reported L2 (comprehension, speaking, and reading) scores are outlined in Table 1 (Appendix F).

--- Insert Table 1 about here --- Musical Background

The participants were all non-musicians, as reflected by the mean years of formal musical training (M = 1.53, SD = 1.76). No statistically significant group differences were found with regards to the years of musical training, p > 0.05. Participants of different languages did not report significantly different music listening habits either, with a mean of 2 hours per day. Cognitive Test Performances

Participants’ performance in the Mottier test, Backward digit span test, along with their years of formal musical training and daily exposure to music are shown in Table 2 (Appendix F).

Mottier test. The conducted ANOVA revealed no statistically significant differences among groups, p = 0.1.

Backward digit span. Results of the ANOVA test showed a significant group difference for the backward digit span scores among groups, F(3,56) = 6.01, p = 0.001. Post-hoc

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comparisons using Bonferroni correction revealed that Mandarin speakers of English scored higher than the other groups. No other group differences were observed.

--- Insert Table 2 about here --- Rhythmic Aptitude

Regarding participants’ rhythmic aptitude skills, the conducted ANCOVA revealed a significant effect of group, F(3,53) = 8.51, p = 0.001. Post-hoc pairwise comparisons using Bonferroni correction revealed a significant difference between the Turkish-English (M =

76.13%) and Dutch-English (M = 66.15%) bilingual groups, Turkish monolinguals (M = 54.36%) and Turkish-English bilinguals, and Turkish monolinguals and Mandarin- English bilinguals (M = 75.64%). No differences between the Dutch-English and Turkish monolingual groups’

performances were found. Pairwise comparisons of groups’ accuracy rates in the rhythmic aptitude test are shown in Figure 1 (Appendix F).

--- Insert Figure 1 about here --- Melodic Aptitude

Results of the ANCOVA conducted with participants’ melodic aptitude performances revealed a significant effect of group, F(3,53) = 4.28, p = 0.009. Post-hoc pairwise comparisons using Bonferroni correction revealed a significant difference only between the Turkish

monolingual (Mean score of correct trials, M = 53.97%) and Mandarin-English bilinguals’ (M = 76.67%) performances. Pairwise comparisons of groups’ accuracy rates in the rhythmic aptitude test are shown in Figure 2 (Appendix F).

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--- Insert Figure 2 about here --- Lexical Tone Discrimination

The results of the ANOVA revealed a significant group difference in the discrimination of both monosyllabic, F(3,59) = 22.99, p = 0.00, and disyllabic lexical tones, F(3,59) = 22.02, p = 0.00. Post-hoc tests with Bonferroni correction showed a significant difference between

English bilinguals (M = 89.87%) and Turkish monolinguals (M = 50.47%), Mandarin-English bilinguals and Turkish-Mandarin-English bilinguals (M = 66.60%), Dutch-Mandarin-English bilinguals (M = 87.33%) and Turkish-English bilinguals, and Dutch-English bilinguals and Turkish monolinguals in the discrimination of monosyllabic tones. In the discrimination of disyllabic tones, pairwise comparisons using Bonferroni correction indicated significant differences between the Mandarin-English bilingual (M = 84.80%) and Turkish monolingual group (M = 50.47%), Dutch-Mandarin-English bilinguals (M = 84.87%) and Turkish monolinguals, and Turkish-English bilinguals (M = 73.13%) and Turkish monolinguals. Comparisons of the groups’ mean accuracy rates in the disyllabic lexical tone discrimination test is shown in Figure 3, and mean accuracy rates in the monosyllabic lexical tone discrimination test in Figure 4 (Appendix F).

--- Insert Figure 3 and 4 about here ---

Discussion

The current study investigated whether speaking a second language enhances individuals’ musical rhythmic and melodic perception. Following Roncaglia-Denissen et al. (2016), we tested Turkish, Dutch, and Mandarin L2 speakers of English, and Turkish monolinguals, on their

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musical rhythmic perception abilities. Participants’ phonological and working memory, as well as their language and music backgrounds were assessed in order to account for individual

differences and control for confounding factors. Furthermore, we extended the previous study by Roncaglia-Denissen et al. (2016) by providing an analysis of the groups’ musical pitch aptitude, with an additional task assessing lexical tone discrimination abilities.

Our findings pointed at the same trend with the Roncaglia-Denissen et al. (2016):

bilinguals scored higher on all musical rhythmic and melodic aptitude tests. However, contrary to Roncaglia-Denissen et al. (2016), our results suggested that speaking a second language brings about an enhancement of musical rhythmic aptitude only if the second language’s rhythmic patterns are different from those of the individual’s native language. The comparison of Dutch-English and Turkish monolingual groups on musical rhythmic aptitude revealed that if the two languages in question are not rhythmically different, mastering these two languages might not boost rhythmic aptitude, as Dutch-English bilinguals did not score significantly higher on the musical rhythmic aptitude test, despite a visible trend. It must be noted that our contrasting results with Roncaglia-Denissen et al. (2016) might be due to the use of different statistical analyses, although highly insignificant differences were observed between the Dutch-English and Turkish monolingual group.

Similar to the findings in the rhythm domain, we found that our only tonal language (Mandarin) speaker group scored the highest on the melody perception and lexical tone discrimination tests. This group was also the only one which significantly outperformed the Turkish monolingual group on melody aptitude. Therefore, with regards to pitch perception, individuals who speak languages which diverge on their respective properties have enhanced perceptual aptitude, similar to the perception of musical rhythms. Moreover, the enhanced melody perception of Mandarin-English speakers compared to the other bilingual groups further

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supports the literature which suggests enhanced pitch perception skills in tonal language speakers (Alexander et al., 2008; Bidelman, Hutka, & Moreno, 2013).

The higher scores in musical aptitude of the bilingual groups in comparison to the Turkish monolingual group might suggest that learning a second language might have an advantageous effect on acoustic perception, and this effect is more nuanced in individuals who speak

rhythmically or melodically dissimilar languages. The enhancing effects of bilingualism are well-documented in different domains of cognition, such as attentional control (Bialystok, 1999), executive functioning (Friesen, Latman, Calvo, & Bialystok, 2015), and inhibitory control (Blumenfeld & Marian, 2011). A similar advantage might be proposed for rhythmic and melodic perception. In the bilingual cognition research, it has been often suggested that bilinguals’

executive functions are improved due to the constant need to monitor their environment to choose which language to use at the moment, and inhibit their immediate language switching response. This might serve as a “training” for the individual’s executive control skills, enhancing the attentional and cognitive control capacities (Bialystok, 1999). Although simultaneous bilinguals significantly excel at such tasks, late bilinguals, who acquired a second language in later ages, outperform monolinguals on inhibitory control and working memory tasks (Bak, Vega-Mendoza, & Sorace, 2014).

This fine-tuning effect of speaking a second language might be available in the perception of musical melodies and rhythms, as well. Learning a second language requires the individual to attend to the rhythmic and melodic patterns of the new language. It is an acoustically demanding process, since the individual has to acquire the rhythmic and prosodic information in the language in order to be a competent speaker of that language. Hence, similar to how bilingualism leads to a training in executive control skills, it might be suggested that speaking a second language

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when learning the new language. This acquisition process might lead the individual to be more attentive to acoustic information, facilitating language recognition and detection.

Rhythmic and melodic information are not only central to language, but also to music. Therefore, as individuals who had acquired a second language become more sensitive to the acoustic details in the input, this sensitivity might be transferred to the musical domain, resulting in a cross-domain acoustic sensitivity across the domains of music and language. Our results point at the possibility of such transfer effects between language and music with respect to rhythmic and melodic information. In this regard, the current study is in line with research suggesting a transfer effect between language and music (Roncaglia-Denissen et al., 2013; Roncaglia-Denissen et al., 2016). Previous research demonstrated the robustness of this effect, since even 9-month-old bilingual infants show heightened acoustic sensitivity to musical contrasts compared to their monolingual peers (Liu & Kager, 2017).

Importantly, however, our results proposed an enhanced rhythmic and melodic aptitude for those individuals whose two languages are rhythmically or melodically different. In rhythmic perception, only the Turkish-English and Mandarin-English bilingual groups, who speak two languages with different rhythmic properties, had significantly higher accuracy compared to Turkish monolinguals. The non-significant enhancement of Dutch-English bilinguals in

comparison to Turkish monolinguals might be due to the overlapping rhythmic properties of the two languages. The same pattern was observed with regards to melodic perception, as only Mandarin-English bilinguals who speak a tonal and a non-tonal language had significantly enhanced pitch accuracy, whereas bilinguals of two non-tonal languages did not have this enhancement. This finding might suggest that the subtle intonation differences between languages might not bring about the same level of sensitivity with speaking a tonal language,

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whose enhancing effects on pitch perception has been demonstrated by numerous studies (e.g. Deutsch, Henthorn, Marvin, & Xu, 2006).

In the current study, we included a lexical tone discrimination test in order to see whether the processing of lexical tones is similar to the processing of musical melodies. If lexical tones and musical melodies were processed employing similar mechanisms, it would be expected that only tonal (Mandarin) language speakers would excel in the lexical tone discrimination test, similar to the results of the MET melody subset. However, all bilingual groups outperformed the Turkish monolingual group in the discrimination of disyllabic lexical tones, with no group effects between the bilingual groups. With regards to monosyllabic tones, the same pattern was

observed, with the Dutch-English group and Mandarin-English group performing better than the Turkish-English bilingual group. This discrepancy between the results of melodic perception and the perception of lexical tones points at the possibility of an interference effect of language. The interesting pattern of results revealing that the Dutch speakers who are naïve to the lexical tones are as accurate as Mandarin speakers was also reflected in previous studies (e.g. Chen et al., 2016), as well as in our informal discussions with other researchers in the field. It is yet to be understood why Dutch speakers, but not English speakers whose language presumably shares the same characteristics with Dutch, excel at the lexical tone discrimination tests. Future research addressing this question is definitely required in order to understand whether Dutch language has a unique aspect which enables its speakers to outperform at this task.

A possible objection to our results would be that the enhanced rhythmic and melodic perception of bilinguals might be due to exposure to musical complexity rather than the effects of bilingualism. According to this alternative account, individuals who speak Turkish, both

monolinguals and bilinguals, should have enhanced musical rhythmic perception abilities, as Turkish music is richer in musical rhythmic complexity with a more frequent use of compound

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meter compared to Western music (Hannon, Soley, & Unnan, 2012). However, this hypothesis is refuted by our Turkish monolingual group’s worse performances in rhythmic perception tests. Turkish bilinguals, who presumably have the same musical background as the Turkish

monolinguals as a result of growing up with a cultural music which is inherently more complex, outperformed Turkish monolinguals on the rhythmic performance tests. Therefore, it may be suggested that learning a second language, rather than having been exposed to rhythmically complex music, influences musical rhythmic perception. Future research on individuals whose traditional music is richer in melodic variations would help us understand whether learning a second language is more salient to musical melodic perception than melodic complexity as well.

Our results point at an effect of bilingualism on the enhancement of musical melody and rhythm at an early perceptual level, in line with what the Musical Ear Test (MET) aims to measure: musical auditory memory. Based on the current findings, it cannot be deduced whether speaking a second language would bring about an improvement at a deeper, higher cognitive level such as the abstraction of musical concepts. While previous research points at bilinguals being more sensitive to musical contrasts (Liu & Kager, 2017), such effects are likely to be at an early perceptual level, and might not be readily reflected at higher cognitive levels indicating musical ability. Future research using tasks such as the Goldsmith Musical Sophistication Index (Müllensiefen, Gingras, Stewart, & Musil, 2014), which require one to employ more musically abstract operations, might demonstrate different results as they capture musical sophistication, an ability different than solely being sensitive to acoustic variations in rhythm and melodies. In this respect, the current study has raised questions in need of further investigation, such as whether the effects of bilingualism revealed at an early perceptual level by our findings would still hold at higher, more abstract levels of musicality.

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All aspects considered, our findings substantiate previous work showing domain-general transfer effects between language and music, but only if the language experience allows for enough variety for acoustic perceptual enhancement. For further research, it would be inspiring to look at languages with different rhythmic and melodic properties, such as Japanese, which is a mora-timed, pitch accent language (Wu, Tu, & Wang, 2012). In pitch-accent languages, pitch is not an integral element to the language, unlike the tones in tonal languages, but accentuates meaning, and gives context. Thus, it would be interesting to see how pitch-accent language speakers perform on musical aptitude tasks. Moreover, our initial results should be validated by further studies with larger sample sizes in order to see whether the observed effects hold on a population-level. Future research addressing these questions will shed light on the role of language experience on musical perception, which would elucidate which linguistic properties are relevant to musical perception, thereby advancing our understanding of the shared

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Appendix A Mottier test Instructions

Dutch

Je zult worden gepresenteerd met gesproken woorden zonder betekenis (bv. turasi). De opdracht is om de woorden exact te herhalen zoals je ze hoort. Na elke opdracht wordt er een nieuw woord gepresenteerd, maar dan met een lettergreep méér. Het eerste woord zal 2 lettergrepen bevatten, het tweede woord 3 lettergrepen, etc. Deze taak duurt ongeveer 10 minuten.

Turkish

Burada size belli bir anlam içermeyen kelimeler söylenecek (örneğin turasi veya bamodeli). Burada yapmanız gereken kelimeleri duyduğunuz anda ve duyduğunuz şekilde tekrar etmeniz. İlk bölüm 2 heceli 6 kelime içerecek, sonraki bölümde 3 heceli 6 kelime olacak. Her bölümden sonra verilecek 6 kelimeye bir hece eklenecek. Bu bölüm yaklaşık 10 dakika sürecek. Eğer sorunuz varsa lütfen bana bildirin. Eğer yoksa, teste başlayalım!

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Appendix B Backward Digit Span Instructions

Dutch

In deze taak zullen wij je reeksen van gesproken cijfers laten horen, die je vervolgens in omgekeerde volgorde dient op te noemen (bijvoorbeeld: 2-1-3 wordt 3-1-2). Wanneer je de cijfers 2-1-3 hoort, zul je deze omgekeerd opnoemen, in dit geval 3-1-2. Deze taak duurt ongeveer 10 minuten.

Na de eerste sessie zullen wij je vragen om een enquête in te vullen over jouw taal- en muzikale achtergrond (of je formele muziekles hebt gehad, of je instrumenten bespeelt, welke talen je spreekt).

Heeft u nog vragen? Zo niet, laten we beginnen met een oefenblok. Druk alstublieft op de spatiebalk.

Turkish

Burada size bir rakam dizisi vereceğiz. Sizin yapmanız gereken, verdiğimiz rakamları tersten söylemek. Örneğin, biz 2-1-3 rakamlarını verdiğimizde, siz 3-1-2 olarak sesli bir şekilde araştırmacıya söyleyeceksiniz. İlk iki dizi iki rakam içerecek, daha sonraki iki dizi üç rakam içerecek. Her iki diziden sonra rakam sayısını birer birer artıracağız. Bu bölüm yaklaşık 10 dakika sürecek.

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Appendix C Musical Ear Test Instructions

Dutch

Musical Ear Test - Melodische Deel:

Deze taak bestaat uit twee delen. In het eerste (melodische) deel zul je gepresenteerd worden met een reeks paren van melodieën. Jouw taak is om te beoordelen of de twee melodieën van het paar identiek zijn of van elkaar verschillen. Dit doe je door op de knoppen “Hetzelfde” of

“Verschillend” te drukken. Antwoord zo snel en accuraat mogelijk als mogelijk door te drukken op de correcte knop. Deze taak duurt ongeveer 10 minuten.

Musical Ear Test - Ritmische Deel:

In het tweede (ritmische) deel zul je gepresenteerd worden met een reeks paren van ritmische frasen. Jouw taak is om, net zoals bij het melodische deel, te beoordelen of de twee ritmes van het paar identiek zijn of van elkaar verschillen. Dit doe je door op de knoppen “Hetzelfde” of

“Verschillend” te drukken. Antwoord zo snel en accuraat mogelijk als mogelijk door te drukken op de correcte knop. Deze taak duurt ongeveer 10 minuten.

Turkish

Bu test 2 bölümden meydana gelecek, melodi bölümü ve ritim bölümü. Melodi bölümünde size çift halinde melodiler sunulacak. Sizin yapmanız gereken bu melodilerin aynı mı farklı mı

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yapabildiğiniz kadar hızlı ve doğru butona tıklamaya çalışarak yapın. Melodi bölümü yaklaşık 10 dakika sürecek.

Ritim görevinde size çift halinde ritimler verilecek. Sizin yapmanız gereken bu iki ritmin aynı mı farklı mı olduğuna karar vermek. Bunu “Same” (Aynı) veya “Different” (Farklı) butonuna

basarak yapacaksınız. Lütfen bunu yapabildiğiniz kadar hızlı ve doğru butona tıklamaya çalışarak yapın. Melodi bölümü yaklaşık 10 dakika sürecek. Sorunuz var mı? Eğer yoksa, hadi başlayalım!

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Appendix D Lexical Tone Test Instructions

This test consists of two parts, one with disyllabic and the other with monosyllabic words. In each part, you will hear 10 different tone bearing syllables respectively for the disyllabic and monosyllabic parts. The to-be-compared stimuli only differ in lexical tones. Your task is to decide whether the two syllables are identical or different. This task will last about 20-25 minutes.

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Appendix E

Self-reported Language Questionnaire Turkish

Kişisel Beyana Dayalı Dil Anketi Q1 Lütfen katılımcı numaranızı girin. Q3 Doğum tarihiniz (gün/ay/yıl) Q4 Cinsiyet

m Kadın m Erkek m Diğer

Q5 Doğduğunuz ülke

Q6 Doğduğunuz ülkede kaç yıl yaşadınız/kaç yıldır yaşıyorsunuz? Q7 Ülkenizde kaç yıl okula gittiniz ya da örgün eğitim aldınız?

Q8 Yabancı bir ülkede kaç yıl okula gittiniz ya da örgün eğitim aldınız? Q9 Mesleğiniz/ öğrenci iseniz bölümünüz

Q10 Aldığınız örgün eğitim/üniversite eğitimi süresi Q11 Lütfen dil yeterliliğinizi değerlendiriniz.

m Yalnızca ana dilimde okuyabiliyor ve yazabiliyorum. m Ana dilim ve başka dil/dillerde okuyabiliyor/yazabiliyorum.

m Çift dilliyim: İkinci dilimde en az ana dilim kadar akıcı konuşabiliyorum. m Çift dilliyim: Çocukluğumda 2 dili aynı anda öğrendim.

m Çok dilliyim: Birden fazla dili ana dilim gibi ya da akıcı konuşabiliyorum ve başka dillere de hakimim.

m Diğer (lütfen belirtiniz) ____________________

Q12 Lütfen anadilinizi kaç yaşınızda öğrendiğinizi, öğrendiğiniz yeri (ev, okul, yurt dışı) ve şu an ana dilinizi ne kadar kullandığınızı (birincil/asıl dil olarak, işte/okulda, ara sıra, vb.) belirtiniz.

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Q14 Lütfen varsa diğer dillerinizi kaç yaşınızda öğrendiğinizi, öğrendiğiniz yeri (ev, okul, yurt dışı) ve şu an ana dilinizi ne kadar kullandığınızı (birincil dil olarak, işte/okulda, ara sıra, vb.) belirtiniz.

Q12 Eğer yaşadığınız ülkeden başka bir ülkede 2 haftadan fazla kaldıysanız, lütfen hangi ülke olduğunu, bu ülkede ne kadar kaldığınızı, o sıradaki yaşınızı ve o ülkede konuştuğunuz dili belirtiniz.

Q13 Lütfen aldığınız standart bir dil sınavı varsa (TOEFL, IELTS vb.) aldığınız puan ile birlikte belirtiniz.

Q14 Okuma: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10 üzerinden değerlendiriniz. Sıradan bir metni (örneğin gazete) okuma ve anlamayı ___________ buluyorum. (1= çok zor; 10=çok kolay)

1 2 3 4 5 6 7 8 9 10 Ana dil m m m m m m m m m m İkinci dil m m m m m m m m m m Diğer dil m m m m m m m m m m

Q15 Yazma: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10 üzerinden değerlendiriniz. Bu dilde fikirlerimi belirtmeyi ___________ buluyorum. (1= çok zor; 10= çok kolay) 1 2 3 4 5 6 7 8 9 10 Ana dil m m m m m m m m m m İkinci dil m m m m m m m m m m Diğer dil m m m m m m m m m m

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Q16 Anlama: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10 üzerinden değerlendiriniz. Sıradan bir konuşma ya da haberleri dinlerken konuşulan dili anlamayı ___________ buluyorum. (1= çok zor; 10= çok kolay)

Q17 Konuşma: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10

üzerinden değerlendiriniz. Ana dili bu dil olan kişiler tarafından doğal bulunacak cümleleri formüle etmek ve sözle ifade etmeyi ___________ buluyorum. (1= çok zor; 10= çok kolay)

Q18 Dil bilgisi: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10 üzerinden değerlendiriniz. Bu dilde bir cümlenin nasıl oluşturulduğunu anlamak bana ___________ geliyor. 1 2 3 4 5 6 7 8 9 10 Ana dil m m m m m m m m m m İkinci dil m m m m m m m m m m Diğer dil m m m m m m m m m m

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Q21 Dil bağımsızlığı: Ana diliniz, ikinci diliniz ve bildiğiniz diğer dillerdeki hakimiyetinizi 10 üzerinden değerlendiriniz. 1= Eğer bu dili kullanırsam, düşüncelerimi önce ana dilime çevirmem gerekir; 10= Bu dilde tamamen bağımsız hissediyorum ve bu dilde düşünebilirim.

Q24 Ana dil ya da ilk akıcı diliniz nedir? Q26 İkinci dil ya da ikinci akıcı diliniz nedir? Q27 Bildiğiniz diğer diller nelerdir?

Q30 Gün içinde en çok hangi dili kullanıyorsunuz? m Ana dil

m İkinci dil

Q31 Konuşmayı öğrendiğinizde ilk olarak hangi dili öğrenmiştiniz? m Ana dil

m İkinci dil

m Her ikisini aynı anda

Q32 Ebeveynlerinizin ana dillerini ve her biriyle hangi dili konuştuğunuzu yazınız. Anne: Ana dil/ konuştuğunuz dil Baba: Ana dil/ konuştuğunuz dil

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Q35 Çocukluğunuzda ikinci bir dil öğrenmediyseniz, ikinci dilinizle ilgili doğru cevapları işaretleyiniz.

q Yabancı dili okulda, yabancı dil dersinde öğrendim. q Bu dili, dilin konuşulduğu bir okulda öğrendim.

q Aile fertleri ya da eş/arkadaşımla iletişimimle öğrendim. q Bir değişim programı sayesinde öğrendim.

q Uzun bir gezide öğrendim.

q Mesleğimden dolayı ya da üniversitede öğrendim. q Diğer (lütfen belirtiniz) ____________________

Q36 Evde ailenizle ya da arkadaşlarınızla en çok hangi dili konuşuyorsunuz? Bu dilleri kiminle konuşuyorsunuz?

Q37 Çocukluğunuzda ana dilinizi en çok hangi ortamda kullandınız? m Evde

m Okulda m Her ikisi de

Q38 Şu an ana dilinizi en çok hangi ortamda kullanıyorsunuz? m Evde

m Okulda m Her ikisi de

Q40 Günün yüzde kaçında bu dilleri kullanıyorsunuz? (Konuşma, Okuma, Yazma, Düşünme) Lütfen Ana dil/ İkinci dil/ Diğer dil(ler) olarak belirtiniz.

Q41 Hangi dilde konuşmayı tercih edersiniz? q Ana dil

q İkinci dil

Q42 Hangi dili duymayı tercih edersiniz? q Ana dil

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Q43 Hangi dilde (kitap, gazete vb.) okumayı tercih edersiniz? q Ana dil

q İkinci dil

Q44 Hangi dilde yazmayı tercih edersiniz? q Ana dil

q İkinci dil

Q45 Kaç yaşında konuşmaya başladınız? Ana dil, ikinci dil ve diğer dil(ler)i ayrı ayrı belirtiniz.

Q46 Kaç yaşında konuşulan cümleleri anlamaya başladınız? Ana dil, ikinci dil ve diğer dil(ler)i ayrı ayrı belirtiniz.

Q47 Kaç yaşında okumaya başladınız? Ana dil, ikinci dil ve diğer dil(ler)i ayrı ayrı belirtiniz. Q48 Kaç yaşında okumaya başladınız? Ana dil, ikinci dil ve diğer dil(ler)i ayrı ayrı belirtiniz. Q56 Ana diliniz ve ikinci diliniz arasında ne kadar sıklıkla geçiş yapıyorsunuz?

1 2 3 4 5 6 7 8 9 10 Asla geçiş yapmıyorum:Çok sık geçiş yapıyorum m m m m m m m m m m

Q57 Diller arasında geçiş yapmak sizin için ne kadar kolaydır?

1 2 3 4 5 6 7 8 9 10 Asla geçiş yapmıyorum:Çok sık geçiş yapıyorum m m m m m m m m m m

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Self-reported Music and Social Background Questionnaire Turkish

Q1 Katılımcı numaranız

Q2 Doğum tarihiniz (gün/ay/yıl) Q3 Cinsiyetiniz

m Kadın m Erkek m Diğer

Q4 Mesleğiniz veya okuyorsanız bölümünüz Q6 Tamamladığınız en yüksek eğitim seviyesi m İlköğretim

m Lise m Üniversite m Yüksek lisans m Doktora

Q7 Eğer hala eğitiminize devam ediyorsanız, devam etmekte olduğunuz eğitim seviyesi m İlköğretim m Lise m Üniversite m Yüksek lisans m Doktora m Öğrenci değilim

Q8 Daha önce okulda veya okul dışında müzik dersi aldınız mı? m Evet

m Hayır

Q9 Müzik dersi almaya kaç yaşında başladınız? Q10 Müzik dersi almayı kaç yaşında bıraktınız?

(45)

Q11 Lütfen aldığınız dersin içeriği hakkında kısaca bilgi veriniz. Eğer bir enstrüman çalmayı öğrendiyseniz hangi enstrüman olduğunu, müzik teorisi (solfej, nota bilgisi vb.) öğrendiyseniz bunları belirtebilirsiniz.

Q12 Daha önce okulda veya okul dışında dans dersi aldınız mı? m Evet

m Hayır

Q13 Kaç yıl dans dersi aldınız? m 1 yıldan az

m 1-2 yıl m 3-5 yıl

m 5 ve daha fazla yıl

Q14 Bir günde ortalama olarak kaç saat müzik dinliyorsunuz?

Q15 Lütfen hangi tür müziği (Klasik müzik, pop müzik, jazz, rock, folk müzik, Türk Halk Müziği vb.) ne kadar dinlediğinizi yüzde olarak belirtiniz. Kendi seçeneklerinizi de ekleyebilirsiniz. Tüm seçeneklerin toplamı %100 olmalıdır.

Q16 Konser veya müzik dinletilerine gider misiniz? m Evet

m Hayır

Q17 Ne sıklıkla konser veya müzik dinletilerine gidersiniz? m Her hafta

m Ayda 1-2 kere m Yılda 2-10 kere m Yılda 2 kereden az

Q18 Hangi türde konser veya müzik dinletilerine gidersiniz? Q19 Sağ elinizi mi sol elinizi mi kullanıyorsunuz?

m Sağ m Sol

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Appendix F Tables and figures Table 1

L2 speaker participants’ self-reported L2 comprehension, speaking and reading skills Mandarin English L2 speakers Turkish English L2 speakers Dutch English L2 speakers L2 English language

skills % Mean SD Mean SD Mean SD

Comprehension 80.66 10.99 81.30 15.98 91.33 10.60

Speaking 78.00 11.46 78.70 16.42 85.33 15.52

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Table 2

Participants’ scores in the Mottier test, Backward digit span, MET melodic and rhythmic subsets, formal musical training, and daily exposure to music

Mandarin English L2 speakers Turkish English L2 speakers Dutch English L2 speakers Turkish monolinguals

Tasks Mean SD Mean SD Mean SD Mean SD

Mottier 25.53 3.79 26.13 5.14 27.40 4.04 23.40 4.30 BDS 10.26 2.84 8.67 2.35 8.00 2.26 6.60 2.09 Melodic aptitude (%) 76.66 6.24 68.08 8.09 68.07 12.54 53.97 9.89 Rhythmic aptitude (%) 75.64 6.15 76.13 9.46 66.15 8.77 54.35 10.31 Formal musical training (years) 1.86 2.77 1.67 1.23 1.40 1.05 1.88 1.44 Daily exposure to music (hours) 2.11 1.99 2.55 1.61 1.42 1.06 1.88 1.44

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Figure 1. Accuracy rates in the rhythmic aptitude test of Mandarin (ME), Turkish (TE), Dutch (DE) L2 learners of English and Turkish monolinguals (TM). Error bars indicate standard errors. (*) denotes statistical significance with p < 0.05.

Figure 1. Accuracy rates in the rhythmic aptitude test of Mandarin (ME), Turkish (TE), Dutch (DE) L2 learners of English and Turkish monolinguals (TM). Error bars indicate standard errors. (*) denotes statistical significance with p < 0.05

*

(49)

Figure 2. Accuracy rates in the melodic aptitude test of Mandarin (ME), Turkish (TE), Dutch (DE) L2 learners of English and Turkish monolinguals (TM). Error bars indicate standard errors. (*) denotes statistical significance with p < 0.05.

*

n.s.

(50)

Figure 3. Accuracy rates in the disyllabic lexical tone discrimination test of Mandarin (ME), Turkish (TE), Dutch (DE) L2 learners of English and Turkish monolinguals (TM). Error bars indicate standard errors. (*) denotes statistical significance with p < 0.05.

*

n.s.

(51)

Figure 4. Accuracy rates in monosyllabic lexical tone discrimination test of Mandarin (ME), Turkish (TE), Dutch (DE) L2 learners of English and Turkish monolinguals (TM). Error bars indicate standard errors. (*) denotes statistical significance with p < 0.05.