Title :
Time-frequency distributions for automatic speech recognition
Author :
Potamianos, Alexandros ; Maragos, Petros
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
3/1/2001 12:00:00 AM
Abstract :
The use of general time-frequency distributions as features for automatic speech recognition (ASR) is discussed in the context of hidden Markov classifiers. Short-time averages of quadratic operators, e.g., energy spectrum, generalized first spectral moments, and short-time averages of the instantaneous frequency, are compared to the standard front end features, and applied to ASR. Theoretical and experimental results indicate a close relationship among these feature sets
Keywords :
Markov processes; feature extraction; spectral analysis; speech recognition; time-frequency analysis; automatic speech recognition; energy spectrum; feature sets; front end features; generalized first spectral moments; hidden Markov classifiers; instantaneous frequency; quadratic operators; short-time averages; spectral moments; time-frequency distributions; Automatic speech recognition; Band pass filters; Context modeling; Frequency estimation; Hidden Markov models; Oscillators; Speech analysis; Speech processing; Speech recognition; Time frequency analysis;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
