Papers with Acoustic Models

2 papers
Exploring the Effect of Dialect Mismatched Language Models in Telugu Automatic Speech Recognition (2022.naacl-srw)

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Challenge: Existing studies have found that the ASR system is susceptible to dialect variations within a language, thereby adversely affecting the APR.
Approach: They propose to build a dialect-specific AM while keeping the Language Model constant for all the dialects and to reduce the degradation by 9% and 15%.
Outcome: The proposed model can be built for three different Telugu regional dialects while keeping the Language Model constant for all the dialects.
Discovering Canonical Indian English Accents: A Crowdsourcing-based Approach (L18-1)

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Challenge: Automated Speech Recognition systems degrade in performance when recognizing accents that are different from the ones in training data.
Approach: They propose to adapt Acoustic Models that are trained on one accent to a target accent by using a small amount of speech data in the target accent.
Outcome: The proposed model can be used to identify accents in Indian English and other languages.

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