Title :
Time-frequency-energy representation based real-time speech recognition
Author :
Wu, Duanpei ; Gowdy, J.N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Clemson Univ., SC, USA
Abstract :
The authors present an approach to isolated-word speech recognition which is characterized by two aspects: (1) nonlinear time normalization based on the gradients of short-time energy in a specific number of frequency bands, which retains the transient portions and ignores the steady-state portions of the speech signal in the frequency domain; and (2) real-time implementation due to low computational load. Simulation has shown that the correct rate of recognition was 99.5% for multiple speakers based on the TI-20 speech database. A very high accuracy for on-line recognition was also obtained
Keywords :
signal representation; speech recognition; time-frequency analysis; TI-20 speech database; frequency bands; frequency domain; isolated-word speech recognition; nonlinear time normalization; on-line recognition; real-time implementation; real-time speech recognition; recognition rate; short-time energy gradients; simulation; speech signal; time-frequency-energy representation; Artificial neural networks; Data mining; Feature extraction; Filter bank; Frequency; Hidden Markov models; Speech processing; Speech recognition; Steady-state; Vocabulary;
Conference_Titel :
Southeastcon '93, Proceedings., IEEE
Conference_Location :
Charlotte, NC
Print_ISBN :
0-7803-1257-0
DOI :
10.1109/SECON.1993.465740
