Automatic phonetic classification of vocalic allophones in Tol
Bibliographic Data
| ID | 22159286 |
|---|---|
| Authors | Marie Bissell (0000-0003-2776-9621, The Ohio State University, corresponding author) |
| Year | 2021 |
| Volume | 6 |
| Issue | 1 |
| Pages | 403 |
| Publication date | 2021-03-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Proceedings of the Linguistic Society of America (JOURNAL) |
| Journal identifiers | ISSN: 2473-8689 • E-ISSN: 2473-8689 |
| Publisher | Linguistic Society of America (PUBLISHER • US) |
| DOI | 10.3765/plsa.v6i1.4977 |
| OpenAlex | W3137008337 |
| Language | EN |
| Citations received | 1 |
| References cited | 13 |
The aim of the present study involving automatic phonetic classification of /e/ and /u/ tokens in Tol is two-fold: first, I test existing claims about allophonic variation within these vowel classes, and second, I investigate allophonic variation within these vowel classes that has yet to be documented. The acoustic phonetic classifications derived in the present study contribute to a more detailed understanding of the allophonic systems operating within the Tol language. Operationalizing machine learning algorithms to investigate under-resourced, indigenous languages has the potential to provide detailed insights into the acoustic phonetic dynamics of a diverse range of vocalic systems
Linguistics · Natural language processing · Operationalization · Speech recognition · Vowel · Computer Science · Engineering · Language and cultural evolution · Music and Audio Processing · Phonetics and Phonology Research · Artificial Intelligence
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,33 |
| Citation span | 2023 - 2023 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |