Abstract
Applies the technique of phone-based acoustic likelihoods to the problem of language identification. The basic idea is to process the unknown speech signal by language-specific phone model sets in parallel, and to hypothesize the language associated with the model set having the highest likelihood. Using laboratory quality speech the language can be identified as French or English with better than 99% accuracy with only as little as 2 seconds of speech. On spontaneous telephone speech from the OGI corpus, the language can be identified as French or English with 82% accuracy with 10 seconds of speech. The 10 language identification rate using the OGI corpus is 59.7% with 10 seconds of signal. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.