Paper Info
Title
Mel, Linear, And Antimel Frequency Cepstral Coefficients In Broad Phonetic Regions For Telephone Speaker Recognition
Abstract
We've examined the speaker discriminative power of melantimel- and linear-frequency cepstral coefficients (MFCCs, a-MFCCs and LFCCs) in the nasal, vowel, and non-nasal consonant speech regions. Our inspiration came from the work of Lu and Dang in 2007. who showed that filterbank energies at sonic frequencies mainly outside the telephone bandwidth possess more speaker discriminative power due to physiological characteristics of speakers, and derived a set of cepstral coefficients that outperformed MFCCs in non-telephone speech. Using telephone speech, we've discovered that LFCCs gave 21.5% and 15.0% relative EER improvements over MFCCs in nasal and non-nasal consonant regions, agreeing with our filterbank energy f-ratio analysis. We've also found that using only the vowel region with MFCCs gives a 9.1% relative improvement over using all speech. Last, we've shown that a-MFCCs are valuable in combination, contributing to a system with 17.3% relative improvement over our baseline.
Year
Venue
Keywords
2009
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5
Speaker recognition, MFCCs, LFCCs, a-MFCCs, filterbank analysis
Field
DocType
Citations 
Consonant,Mel-frequency cepstrum,Pattern recognition,Computer science,Filter bank,Speech recognition,Speaker recognition,Speaker diarisation,Artificial intelligence,Vowel,Discriminative model
Conference
10
PageRank 
References 
Authors
0.67
5
2
Name
Order
Citations
PageRank
Howard Lei11126.90
Eduardo López2346.74