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Why a Rising Tone is Falling in Mandarin Sentences

This symposium explores the discrepancies between lexical tone specifications and observed sentence productions in Mandarin. It aims to understand the difference between lexical tones and sentence production, and proposes a simulation model linking phonology to phonetics.

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Why a Rising Tone is Falling in Mandarin Sentences

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  1. Why a Rising Tone is Falling in Mandarin Sentences Word Accents and Tones in Sentence Perspective: A symposium in conjunction with the 60th birthday of Professor Gösta Bruce Chilin Shih University of Illinois at Urbana-Champaign January 10, 2007 Lund, Sweden

  2. Generated by WordsEye from text description. Under development at SemanticLight, Inc.

  3. Outline • What we know • Chinese is a lexical tone language. • Surprise! • Tones in sentences may deviate considerably from their lexical specifications. • Research question • Explain the difference between lexical tones and the observed sentence production. • Implication • A simulation model linking phonology to phonetics.

  4. Chinese Lexical Tones Tone shapes differentiate lexical meaning. Ma1: mother Ma2: hemp Ma3: horse Ma4: to scold

  5. Chinese Sentences Ma1-ma0 ma4 ma3. Mother scolds the horse. Ma3 ma4 ma1-ma0. The horse scolds mother.

  6. Chinese Intonation Types (Data from JiahongYuan) Statement Li3bai4wu3 Luo2yan4 yao4 mai3 lu4. On Friday Luoyan wants to buy a deer. Question

  7. Classification of Tone Shapes Tone 1 High level Tone 2 Rising Tone 3 Low falling Tone 4 High falling

  8. Cause of Tonal Distortion • Ease of articulatory effort • Balancing articulatory effort and communication need

  9. Physiological constraints: Communication errors: • When you say what you think • you are saying: • When you are not saying want you • think you are saying:

  10. Ease of Articulatory Effort—I

  11. Ease of Articulatory Effort—II

  12. Ease of Articulatory Effort—III

  13. Production of Rising and Falling Tones

  14. Severe Tonal Distortion—I

  15. People Talk Nearly As Fast As Possible

  16. Severe Tonal Distortion—II

  17. Local distortion is predictable from global optimization

  18. A Racing Game

  19. Adjusting the Best Path

  20. Best Path in Tonal Production 0.5 1.0 1.0 0.0 1.0

  21. Stem-ML • The prosodic modeling is based on Stem-ML (Soft Template Mark-up Language). • Stem-ML consists of a set of mathematically defined tags with value attributes. For example: Tone prosodic strength • Allowing user-defined accent shapes, phrase curves, and other speaker specific parameters. Kochanski and Shih (2003), Prosody modeling with soft templates, Speech Communication V. 39. Shih (in preparation), Prosody Learning and Generation, Springer.

  22. Basic Assumptions • Pre-planning. • Balance articulatory effort and communication needs (Lindblom, Ohala). • A dynamical model for the muscles that control f0 (Hill).

  23. We further propose: • Speaker shifts weights dynamically • as they speak. • This is the prosodic strength, • which reflects the articulatory effort.

  24. Linking Phonology and Phonetics • A model is a sequence of templates (i.e. points representing tone/accent shapes). The templates encodes phonological information. • For tone languages, there is one template per tone. Templates are stretched to fit duration. • Each template has a strength. The strength value determines phonetic variation.

  25. Representation • Surface F0 contours are coded as a set of Template strength T11.0 T3 0.3 T4 1.2 T5 0.8 T21.0 T1 0.5 • Generation: Template strengthF0 • Learning: Template, F0 Template strength

  26. Modeling Math (Credit to Greg Kochanski) “Effort” is the muscle tension (~frequency) at time t. Each target encodes some linguistic information, ri is the error of the ith target, and si is its importance. “Error” y is the ith pitch target and a bar denotes an average over a target.

  27. Representing F0 As Tone Strength

  28. Simulation of Tonal Production—I

  29. Simulation of Tonal Production—II

  30. Model Fits to Mandarin Chinese 0.61 free parameters per syllable, 13 Hz RMS error.

  31. Works for English The highest f0 is on a weak, unaccented word. would I like Uhm A flight to Seattle from Albuquerque

  32. Muscle Dynamics Interpolation

  33. Discourse Functions • Topic initialization • Discourse structure • Phrasing • Emphasis • New vs. old information • Other communicative means

  34. How Do They Fit Together?

  35. Conclusion • Speech is a communication system. Speakers balance articulatory effort and communication needs. • We need a representation that encodes • Accent template • Articulatory effort • Emotional State • We present a computational simulation model that generate surface phonetic variations from this representation.

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