For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
N-Gram Modeling Based on Recognized Phonemes in Automatic Language Identification
Hingkeung KWAN Keikichi HIROSE
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1998/11/25
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Speech Processing and Acoustics
language identification, N-gram, phoneme, recognized labels, mixed phoneme recognition (MPR),
Full Text: PDF(625.8KB)>>
Due to a rather low phoneme recognition rate for noisy telephone speech, there may arise large differences between N-gram built upon recognized phoneme labels and those built upon original attached phoneme labels, which in turn would affect the performances of N-gram based language identification methods. Use of N-gram built upon recognized phoneme labels from the training data was evaluated and was shown to be more effective for the language identification. The performance of mixed phoneme recognizer, in which both language-dependent and language-independent phonemes were included, was also evaluated. Results showed that the performance was better than that using parallel language-dependent phoneme recognizers in which bias existed due to different numbers of phonemes among languages.