Title :
Language identification using phone-based acoustic likelihoods
Author :
Lamel, L.F. ; Gauvain, J.-L.
Author_Institution :
LIMSI-CNRS, Orsay, France
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
Keywords :
hidden Markov models; learning (artificial intelligence); maximum likelihood estimation; natural languages; neural nets; speech processing; speech recognition; English; French; OGI corpus; highest likelihood; identification rate; laboratory quality speech; language identification; phone-based acoustic likelihoods; spontaneous telephone speech; unknown speech; Airports; Character recognition; Hidden Markov models; Laboratories; Natural languages; Neural networks; Signal processing; Speech processing; Speech recognition; Telephony;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389297