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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2408.05641 |
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| _version_ | 1866917746197921792 |
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| author | Fan, Chaofei Henderson, Jaimie M. Manning, Chris Willett, Francis R. |
| author_facet | Fan, Chaofei Henderson, Jaimie M. Manning, Chris Willett, Francis R. |
| contents | Prior coarticulation studies focus mainly on limited phonemic sequences and specific articulators, providing only approximate descriptions of the temporal extent and magnitude of coarticulation. This paper is an initial attempt to comprehensively investigate coarticulation. We leverage existing Electromagnetic Articulography (EMA) datasets to develop and train a phoneme-to-articulatory (P2A) model that can generate realistic EMA for novel phoneme sequences and replicate known coarticulation patterns. We use model-generated EMA on 9K minimal word pairs to analyze coarticulation magnitude and extent up to eight phonemes from the coarticulation trigger, and compare coarticulation resistance across different consonants. Our findings align with earlier studies and suggest a longer-range coarticulation effect than previously found. This model-based approach can potentially compare coarticulation between adults and children and across languages, offering new insights into speech production. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_05641 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model Fan, Chaofei Henderson, Jaimie M. Manning, Chris Willett, Francis R. Audio and Speech Processing Prior coarticulation studies focus mainly on limited phonemic sequences and specific articulators, providing only approximate descriptions of the temporal extent and magnitude of coarticulation. This paper is an initial attempt to comprehensively investigate coarticulation. We leverage existing Electromagnetic Articulography (EMA) datasets to develop and train a phoneme-to-articulatory (P2A) model that can generate realistic EMA for novel phoneme sequences and replicate known coarticulation patterns. We use model-generated EMA on 9K minimal word pairs to analyze coarticulation magnitude and extent up to eight phonemes from the coarticulation trigger, and compare coarticulation resistance across different consonants. Our findings align with earlier studies and suggest a longer-range coarticulation effect than previously found. This model-based approach can potentially compare coarticulation between adults and children and across languages, offering new insights into speech production. |
| title | Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2408.05641 |