Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model

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.

Authors

Publication Details

Published
2024-09-01
DOI
https://doi.org/10.21437/interspeech.2024-2191
Citations
2
Primary Topic
Phonetics and Phonology Research
Type
article
Field-Weighted Citation Impact
1.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model

Jaimie M. Henderson, Christopher D. Manning, Francis R. Willett, Chaofei Fan
2 citations
Phonetics and Phonology Research
1.02
article

Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model

Jaimie M. Henderson, Christopher D. Manning, Francis R. Willett, Chaofei Fan
article en
2 citations

Abstract

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.

National Institutes of Health, Wu Tsai Neurosciences Institute, Stanford University, National Institute on Deafness and Other Communication Disorders
Reduced inequalities
Openalex Percentile: Top 22%
Phonetics and Phonology Research
1.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.