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Topics in the Study of the Pragmatic Functions of Phonetic Reduction in Dialog

Nigel G. Ward, Carlos A. Ortega

TL;DR

This work addresses the gap in understanding how phonetic reduction operates pragmatically in dialog. It combines annotation-driven data collection with a baseline feature-based predictive attempt to detect reduction, revealing that dialog reduction correlates with high pitch, wide pitch range, and intensity rather than the read-speech correlates, and that simple acoustic features yield only modest predictive power (English $0.24$, Spanish $0.17$). It also expands the functional landscape by detailing nine potential pragmatic functions associated with reduction in English and reports cross-language differences, including Spanish tendencies where negative assessments can be reduced. Overall, the study provides a publicly accessible annotated corpus for perceived reduction, shows the limitations of linear-feature detectors for dialog, and offers guidance for future work that may leverage speech recognition or pretrained models to better capture reduction patterns and their pragmatic roles in conversation.

Abstract

Reduced articulatory precision is common in speech, but for dialog its acoustic properties and pragmatic functions have been little studied. We here try to remedy this gap. This technical report contains content that was omitted from the journal article (Ward et al. 2024, submitted). Specifically, we here report 1) lessons learned about annotating for perceived reduction, 2) the finding that, unlike in read speech, the correlates of reduction in dialog include high pitch, wide pitch range, and intensity, and 3) a baseline model for predicting reduction in dialog, using simple acoustic/prosodic features, that achieves correlations with human perceptions of 0.24 for English, and 0.17 for Spanish. We also provide examples of additional possible pragmatic functions of reduction in English, and various discussion, observations and speculations

Topics in the Study of the Pragmatic Functions of Phonetic Reduction in Dialog

TL;DR

This work addresses the gap in understanding how phonetic reduction operates pragmatically in dialog. It combines annotation-driven data collection with a baseline feature-based predictive attempt to detect reduction, revealing that dialog reduction correlates with high pitch, wide pitch range, and intensity rather than the read-speech correlates, and that simple acoustic features yield only modest predictive power (English , Spanish ). It also expands the functional landscape by detailing nine potential pragmatic functions associated with reduction in English and reports cross-language differences, including Spanish tendencies where negative assessments can be reduced. Overall, the study provides a publicly accessible annotated corpus for perceived reduction, shows the limitations of linear-feature detectors for dialog, and offers guidance for future work that may leverage speech recognition or pretrained models to better capture reduction patterns and their pragmatic roles in conversation.

Abstract

Reduced articulatory precision is common in speech, but for dialog its acoustic properties and pragmatic functions have been little studied. We here try to remedy this gap. This technical report contains content that was omitted from the journal article (Ward et al. 2024, submitted). Specifically, we here report 1) lessons learned about annotating for perceived reduction, 2) the finding that, unlike in read speech, the correlates of reduction in dialog include high pitch, wide pitch range, and intensity, and 3) a baseline model for predicting reduction in dialog, using simple acoustic/prosodic features, that achieves correlations with human perceptions of 0.24 for English, and 0.17 for Spanish. We also provide examples of additional possible pragmatic functions of reduction in English, and various discussion, observations and speculations
Paper Structure (34 sections, 5 figures, 6 tables)

This paper contains 34 sections, 5 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Related Research
  3. Phonetic and Phonological Correlates
  4. Methods of Investigation
  5. Other Interesting Related Research
  6. Annotating for Perceived Reduction
  7. Inter-Annotator Agreement
  8. Possible Revisions to the Guidelines and Procedure
  9. Features and Correlations
  10. Features Considered
  11. Correlations
  12. Predictive Models
  13. More on the Functional Annotation Process
  14. The Initial List
  15. The First-Pass Annotation
  16. ...and 19 more sections

Figures (5)

  • Figure 1: Count of labels for English (left) and Spanish (right)
  • Figure 2: Inter-annotator confusion matrix, across both EN and ES labels
  • Figure 3: Stimulus screen. For each word, subjects could play the reference and the first and second conversational renditions.
  • Figure 4: Feature correlations with reduction for English
  • Figure 5: Feature correlations with reduction for Spanish