JOURNAL ARTICLE

Noise Robust Speech Features for Automatic Continuous Speech Recognition using Running Spectrum Analysis

Abstract

In this report, new robust speech feature is introduced and applied for an automatic continuous speech recognition system. Using these features, the noise robust continuous speech recognition can be realized. The new running spectrum analysis (RSA) method is used in order to remove un-speech components over 15 Hz in modulation spectrum domain. Using RSA, speech features are emphasized for the design of tri-phone HMM where the tri-phone HMM is used in continuous speech recognition. In order to show the performance of the developed system, some comparisons with conventional one are given in experiments.

Keywords:
Speech recognition Computer science Hidden Markov model Voice activity detection Phone Noise (video) Speech processing Pattern recognition (psychology) Feature extraction Artificial intelligence

Metrics

3
Cited By
0.00
FWCI (Field Weighted Citation Impact)
9
Refs
0.20
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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