JOURNAL ARTICLE

Non-native Accent Pronunciation Modeling in Automatic Speech Recognition

Abstract

In this paper, we proposed an approach to model the pronunciation of non-native accented speech for automatic speech recognition system. The proposed method consists of two phases: phones adaptation and pronunciation generalization. In phones adaptation, we identify the phones used by non-native speakers compared to the standard phones, and then remove the mismatch, as a result of the influence from mother tongue. In pronunciation adaptation, we predict the pronunciations of words by non-native speakers. The results shown the proposed approach reduce the WER from 44.8% to 41.9%.

Keywords:
Pronunciation Speech recognition Computer science Stress (linguistics) Adaptation (eye) Generalization First language Natural language processing Artificial intelligence Acoustic model Speech processing Linguistics Psychology Mathematics

Metrics

5
Cited By
1.18
FWCI (Field Weighted Citation Impact)
16
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Phonetics and Phonology Research
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
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