Tone

Yip, Moira

doi:10.1017/cbo9780511486371.011

Cited by 43 publications

(57 citation statements)

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“…This practice is based on previous evidence that the entire syllable is the tone-bearing unit Wong and Xu, 2007;Xu, 1998). However, because there is no F 0 during a voiceless consonant, it is also reasonable to assume that voiceless intervals are irrelevant for realizing underlying tonal contours, as has been argued based on phonetic data (Howie, 1974;Rose, 1988), and assumed in some phonological accounts of tone (Duanmu, 2000;Yip, 2002;Zhang, 2004). More frequently, the issue of the exact temporal interval of tonal unit is left vague.…”

Section: Case Study B: Target Bearing Unit -Rhyme Vs Syllablementioning

confidence: 98%

Toward invariant functional representations of variable surface fundamental frequency contours: Synthesizing speech melody via model-based stochastic learning

Prom-on

2014

Speech Communication

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Variability has been one of the major challenges for both theoretical understanding and computer synthesis of speech prosody. In this paper we show that economical representation of variability is the key to effective modeling of prosody. Specifically, we report the development of PENTAtrainer -A trainable yet deterministic prosody synthesizer based on an articulatory-functional view of speech. We show with testing results on Thai, Mandarin and English that it is possible to achieve high-accuracy predictive synthesis of fundamental frequency contours with very small sets of parameters obtained through stochastic learning from real speech data. The first key component of this system is syllable-synchronized sequential target approximation -implemented as the qTA model, which is designed to simulate, for each tonal unit, a wide range of contextual variability with a single invariant target. The second key component is the automatic learning of function-specific targets through stochastic global optimization, guided by a layered pseudo-hierarchical functional annotation scheme, which requires the manual labeling of only the temporal domains of the functional units. The results in terms of synthesis accuracy demonstrate that effective modeling of the contextual variability is the key also to effective modeling of function-related variability. Additionally, we show that, being both theory-based and trainable (hence datadriven), computational systems like PENTAtrainer can serve as an effective modeling tool in basic research, with which the level of falsifiability in theory testing can be raised, and also a closer link between basic and applied research in speech science can be developed.3 Graphical Abstract Highlights (maximum 85 characters/bullet)• High synthetic accuracy of prosody achieved for Thai, Mandarin and English • Many-to-one mapping from contextually variable surface F 0 to invariant functional targets • Effectively handling of both contextual and non-contextual variability • Combination of deterministic synthesis and data-driven parameter learning • Large-scale and full-detailed prosody synthesis as tool for theory testing • Freely available as a Praat scripts and plug-ins to the speech science community at large

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Section: Case Study B: Target Bearing Unit -Rhyme Vs Syllablementioning

confidence: 98%

Toward invariant functional representations of variable surface fundamental frequency contours: Synthesizing speech melody via model-based stochastic learning

Prom-on

2014

Speech Communication

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“…Tone languages exploit variations in pitch at the syllable level to signal differences in word meaning (Yip 2003). The bulk of information on tonal processing in the brain comes primarily from two tone languages: Mandarin Chinese, which has four contrastive tones, and Thai, which has five (for reviews, see Gandour (1998Gandour ( , 2006a).…”

Section: Evidence For An Interaction Between Processing Of Pitch Infomentioning

confidence: 99%

Neural specializations for speech and pitch: moving beyond the dichotomies

Zatorre¹,

Gandour

2007

Phil. Trans. R. Soc. B

327

262

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The idea that speech processing relies on unique, encapsulated, domain-specific mechanisms has been around for some time. Another well-known idea, often espoused as being in opposition to the first proposal, is that processing of speech sounds entails general-purpose neural mechanisms sensitive to the acoustic features that are present in speech. Here, we suggest that these dichotomous views need not be mutually exclusive. Specifically, there is now extensive evidence that spectral and temporal acoustical properties predict the relative specialization of right and left auditory cortices, and that this is a parsimonious way to account not only for the processing of speech sounds, but also for non-speech sounds such as musical tones. We also point out that there is equally compelling evidence that neural responses elicited by speech sounds can differ depending on more abstract, linguistically relevant properties of a stimulus (such as whether it forms part of one's language or not). Tonal languages provide a particularly valuable window to understand the interplay between these processes. The key to reconciling these phenomena probably lies in understanding the interactions between afferent pathways that carry stimulus information, with top-down processing mechanisms that modulate these processes. Although we are still far from the point of having a complete picture, we argue that moving forward will require us to abandon the dichotomy argument in favour of a more integrated approach.

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“…This sets the account apart from the original proposal of Gradient Symbolic Representations in Smolensky & Goldrick (2016);Rosen (2016). Apart from this new representational assumptions of gradient acitvity, the analysis is based primarily on standard constraints on tone structures (cf., for example, Yip, 2002) -the assumption of Gradient Symbolic Representations hence allows to predict a wide variety of apparent exceptionality patterns from a single and rather simple phonology.…”

Section: Resultsmentioning

confidence: 99%

Being exceptional is being weak: Tonal exceptions in San Miguel el Grande Mixtec

Zimmermann

2018

AMP

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The assumption of Gradient Symbolic Representations (Smolensky & Goldrick 2016; Rosen 2016) allows a unified account of lexical exceptions to phonological generalizations or processes. It states that phonological elements can have different degrees of presence in an underlying representation, expressed as numerical activities. In this paper, I strengthen the argument for Gradient Symbolic Representations and provide a case study of two seemingly unrelated exceptions in the tonal phonology of San Miguel el Grande Mixtec that receive a unified explanation under the assumption of gradient activity. In addition, I argue for a modification of the original Gradient Symbolic Representation assumption and propose the existence of gradient activity in the output. This assumption allows to predict markedness-driven exceptionality patterns that remain unexplained in the original proposal.

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Tone

Cited by 43 publications

References 0 publications

Toward invariant functional representations of variable surface fundamental frequency contours: Synthesizing speech melody via model-based stochastic learning

Toward invariant functional representations of variable surface fundamental frequency contours: Synthesizing speech melody via model-based stochastic learning

Neural specializations for speech and pitch: moving beyond the dichotomies

Being exceptional is being weak: Tonal exceptions in San Miguel el Grande Mixtec

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