Abstract
The prosodic structure of speech and the redundancy of words can significantly strengthen or weaken segmental articulation. This paper investigates the acoustic effects of lexical stress, intra-word location, and predictability on sentence internal intervocalic consonants from accented words, using meaningful reading materials from 4157 sentences read by two American English speakers. Consonant duration and spectral balance in such reading materials show reduction in unstressed consonants and in consonants occurring later in the word (Initial vs. Medial vs. Final). Coronal consonants behaved distinctly, which was interpreted as a shift from full to flap or tap articulation in a subset of the phoneme realizations. This shift in articulation, and part of the consonant specific acoustic variation, could be linked to the frequency distribution of consonant classes over the investigated conditions. A higher frequency of occurrence of a consonant class in our corpus and a CELEX word-list was associated with shorter durations and differences in spectral balance that would increase the communicative efficiency of speech.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 100-123 |
| Number of pages | 24 |
| Journal | Speech Communication |
| Volume | 47 |
| Issue number | 1-2 |
| DOIs | |
| State | Published - Jan 1 2005 |
Funding
This research was made possible by grants 300-173-029, 355-75-001, and 276-75-002 of the Netherlands Organization for Scientific Research (NWO). NWO also supplied the additional funding which made this collaboration possible. This work was partly performed at Bell Labs, Lucent Technologies, Murray Hill NJ, USA. We would like to thank the anonymous reviewers for their many detailed and helpful comments.
| Funders |
|---|
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek |
Keywords
- Acoustic reduction
- Prosodic structure
- Redundancy
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Communication
- Language and Linguistics
- Linguistics and Language
- Computer Vision and Pattern Recognition
- Computer Science Applications
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