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Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
Published on: September 27, 2024
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Extreme stop allophony in Mixtec spontaneous speech: data, word prosody, and modelling
Christian DiCanio1,2, Wei-Rong Chen2, Joshua Benn1
1Department of Linguistics, University at Buffalo, Buffalo NY 14260, USA.
Summary
Consonants in Yoloxóchitl Mixtec undergo lenition, particularly in word-medial pre-tonic positions, showing increased voicing and duration. This study also models these phonological patterns using deep neural networks.
Area of Science:
- Phonetics and Phonology
- Linguistic Anthropology
- Computational Linguistics
Background:
- Word-level prosody influences consonant lenition, typically strengthening initial consonants and weakening medial ones.
- Yoloxóchitl Mixtec, an endangered Mexican language, displays significant lenition in voiceless consonants, even in careful speech.
Purpose of the Study:
- To investigate the relationship between word-prosodic position and obstruent lenition in Yoloxóchitl Mixtec.
- To analyze consonant duration, voicing, and manner of articulation in relation to prosodic context.
- To develop computational models for predicting lenition patterns.
Main Methods:
- Analysis of a spontaneous speech corpus of Yoloxóchitl Mixtec.
- Examination of consonant duration, passive voicing, and manner of articulation.
- Application of deep neural networks for pattern modeling and categorization.
Main Results:
- Word-medial pre-tonic position is identified as the primary site for consonant lengthening and reduced voicing.
- Non-pre-tonic consonants exhibit greater voicing and shorter duration.
- Morpheme functional status influences voicing lenition; word-medial pre-tonic stops show more complete closure than non-pre-tonic stops.
Conclusions:
- The study confirms specific prosodic positions driving consonant lenition in Yoloxóchitl Mixtec.
- Findings align with broader research on phonetics of lenition and offer computational tools for analysis.
- The research contributes to understanding endangered languages and developing predictive models for phonological processes.
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