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Chapter 12. From pitch stylization to automatic tonal annotation of speech corpora

  • Piet Mertens
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Rhapsodie
This chapter is in the book Rhapsodie

Abstract

This chapter proposes a labeling scheme for pitch-related aspects of speech prosody and describes an automatic annotation system using this scheme.

In the labelling scheme, the fine-grained transcription provides labels indicating the pitch level and pitch movement of individual syllables. The pitch levels “bottom” and “top” indicate the boundaries of the speaker’s pitch range. Three additional levels – “low”, “mid”, “high” – are defined on the basis of pitch changes in the local context. For pitch movements, both simple and compound, the transcription indicates direction (rise, fall, level) and size (large and small melodic intervals), using size categories adjusted to the speaker’s pitch range.

The automatic tonal annotation system combines several processing steps: segmentation into syllabic nuclei, pause detection, pitch stylization, pitch range estimation, pitch movement classification, and pitch level assignment. It uses a rule-based procedure, which unlike commonly used supervized learning techniques does not require a labelled corpus to train the model.

Abstract

This chapter proposes a labeling scheme for pitch-related aspects of speech prosody and describes an automatic annotation system using this scheme.

In the labelling scheme, the fine-grained transcription provides labels indicating the pitch level and pitch movement of individual syllables. The pitch levels “bottom” and “top” indicate the boundaries of the speaker’s pitch range. Three additional levels – “low”, “mid”, “high” – are defined on the basis of pitch changes in the local context. For pitch movements, both simple and compound, the transcription indicates direction (rise, fall, level) and size (large and small melodic intervals), using size categories adjusted to the speaker’s pitch range.

The automatic tonal annotation system combines several processing steps: segmentation into syllabic nuclei, pause detection, pitch stylization, pitch range estimation, pitch movement classification, and pitch level assignment. It uses a rule-based procedure, which unlike commonly used supervized learning techniques does not require a labelled corpus to train the model.

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