DocumentCode
2323960
Title
Ear-model derived features for automatic speech recognition
Author
de Mori, Renato ; Albesano, Dario ; Gemello, Roberto ; Mana, Franco
Author_Institution
LIA CERI-IUP, Univ. of Avignon, France
Volume
3
fYear
2000
fDate
2000
Firstpage
1603
Abstract
The paper provides a theoretical justification that gravity centers (GC) in frequency bands computed from zero-crossing information are far more robust to additive telephone noise than GCs computed from FFT spectra. Experiments on two different corpora confirm the theoretical results when GCs are added to standard mel frequency-scaled cepstral coefficients (MFCC) and their time derivatives. A 20.1% word error reduction is observed on a large telephone corpus of Italian cities, with an average signal-to-noise ratio (SNR) of 15 dB, if GCs are computed from zero-crossings, while performance deteriorates when GCs are computed from FFT spectra
Keywords
acoustic noise; cepstral analysis; speech recognition; FFT spectra; Italian cities; SNR; additive telephone noise; automatic speech recognition; average signal-to-noise ratio; ear-model derived features; frequency bands; gravity centers; large telephone corpus; performance; standard mel frequency-scaled cepstral coefficients; time derivatives; word error reduction; zero-crossing information; Additive noise; Automatic speech recognition; Cepstral analysis; Frequency; Gravity; Hidden Markov models; Neural networks; Noise robustness; Telecommunication computing; Telephony;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location
Istanbul
ISSN
1520-6149
Print_ISBN
0-7803-6293-4
Type
conf
DOI
10.1109/ICASSP.2000.862002
Filename
862002
Link To Document