Syllable synchronization and the P-center in Cantonese

Chow, Ivan; Belyk, Michel; Tran, Vance; Brown, Steven

doi:10.1016/j.wocn.2014.10.006

Cited by 11 publications

(3 citation statements)

References 46 publications

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“…For example, the location of the P-center in speech is known to be dependent on various factors such as the duration of phonemic elements (e.g. vowel, consonant) and the type of the syllable-initial consonant (Barbosa et al, 2005;Chow et al, 2015;Cooper et al, 1986;Villing, 2010). Therefore, rather than building an objective definition of sound onset, we ask each participant to reflect on their interpretation of acoustic units of their song and speech focusing on the P-center.…”

Section: Methods 21 Recording and Segmentation Protocolmentioning

confidence: 99%

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

Ozaki¹,

Tierney²,

Pfordresher³

et al. 2022

Preprint

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What, if any, similarities and differences between song and speech are consistent across cultures? Both song and speech are found in all known human societies and are argued to share evolutionary roots and cognitive resources, yet no studies have compared similarities and differences between song and speech across languages on a global scale. We will compare sets of matched song/speech recordings produced by our 81 coauthors whose 1st/heritage languages span 23 language families. Each recording set consists of singing, recited lyrics, and spoken description, plus an optional instrumental version of the sung melody to allow us to capture a “musi-linguistic continuum” from instrumental music to naturalistic speech. Our literature review and pilot analysis using five audio recording sets (by speakers of Japanese, English, Farsi, Yoruba, and Marathi) led us to make six predictions for confirmatory analysis comparing song vs. spoken descriptions: three consistent differences and three consistent similarities. For differences, we predict that: 1) songs will have higher pitch than speech, 2) songs will be slower than speech, and 3) songs will have more stable pitch than speech. For similarities, we predict that 4) pitch interval size, 5) timbral brightness, and 6) pitch declination will be similar for song and speech. Because our opportunistic language sample (approximately half are Indo-European languages) and unusual design involving coauthors as participants (approximately 1/5 of coauthors had some awareness of our hypotheses when we recorded our singing/speaking) could affect our results, we will include robustness analyses to ensure our conclusions are robust to these biases, should they exist. Other features (e.g., rhythmic isochronicity, loudness) and comparisons involving instrumental melodies and recited lyrics will be investigated through post-hoc exploratory analyses. Our sample size of n=80 people providing sung/spoken recordings already exceeds the required number of recordings (i.e. 60) to achieve 95% power with the alpha level of 0.05 for the hypothesis testing of the selected six features. Our study will provide diverse cross-linguistic empirical evidence regarding the existence of cross-cultural regularities in song and speech, shed light on factors shaping humanity’s two universal vocal communication forms, and provide rich cross-cultural data to generate new hypotheses and inform future analyses of other factors (e.g., functional context, sex, age, musical/linguistic experience) that may shape global musical and linguistic diversity.

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Section: Methods 21 Recording and Segmentation Protocolmentioning

confidence: 99%

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

Ozaki¹,

Tierney²,

Pfordresher³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The rhythmic transcriptions segmented sentences into a series of stress groups, or what we shall refer to as “prominence groups” (PG), akin to measures of music. We use the term “prominence group” rather the “stress group” in order to accommodate languages such as Cantonese that have no word-level stress but that instead have points of prominence at the sentence level (Chow, Belyk, Tran, & Brown, 2015). This is formally analogous to the rhythmic units proposed in isochrony models of speech rhythm, although our groupings need not be isochronous throughout a sentence (see below).…”

Section: Methodsmentioning

confidence: 99%

A musical model of speech rhythm.

Brown¹,

Pfordresher²,

Chow³

2017

Psychomusicology: Music, Mind, and Brain

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Research on speech rhythm has been notoriously oblivious to describing actual rhythms in speech. We present here a model of speech rhythm at the sentence level inspired by musical conceptions of meter. We posit that speech is underlain by a basic metricality. However, instead of arguing that speech is isochronous, we propose that utterances can have internal changes of meter, making them “heterometric.” In addition, we see 2 rhythmic devices for obviating the need for meter changes within utterances and thus maintaining the stability of the rhythm. Both of them involve subdivisions of component beats into subbeats: 1) subdivisions into 2’s and 3’s, resulting in duplets and triplets, respectively; and 2) subdivisions according to complex ratios, resulting in polyrhythms. We tested the model acoustically by having a group of 14 participants read unfamiliar sentences aloud and examining the extent to which their timing conformed with the predictions of a priori rhythmic transcriptions of the sentences. The observed patterns of variability in speech timing for these sentences, when measured at the bar level of the transcription, were generally consistent with the musical model.

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“…Both acoustic and perceptual studies (e.g. [9,10,11,12]) have found the factors influencing the locations of P-centres to be the phonological structure of syllables. In a syllable consisting of a syllable-initial consonant and a subsequent vowel, the P-centre is usually close to the vowel onset [13,14,15].…”

Section: Linguistics Backgroundmentioning

confidence: 99%

Synchronising speech segments with musical beats in Mandarin and English singing

Zhang¹,

Zhu²

2021

Preprint

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Generating synthesised singing voice with models trained on speech data has many advantages due to the models' flexibility and controllability. However, since the information about the temporal relationship between segments and beats are lacking in speech training data, the synthesised singing may sound off-beat at times. Therefore, the availability of the information on the temporal relationship between speech segments and music beats is crucial. The current study investigated the segment-beat synchronisation in singing data, with hypotheses formed based on the linguistics theories of P-centre and sonority hierarchy. A Mandarin corpus and an English corpus of professional singing data were manually annotated and analysed. The results showed that the presence of musical beats was more dependent on segment duration than sonority. However, the sonority hierarchy and the P-centre theory were highly related to the location of beats. Mandarin and English demonstrated cross-linguistic variations despite exhibiting common patterns.

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Syllable synchronization and the P-center in Cantonese

Cited by 11 publications

References 46 publications

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

A musical model of speech rhythm.

Synchronising speech segments with musical beats in Mandarin and English singing

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