Comparison between different feature extraction techniques for audio-visual speech recognition

Multimodal Feature Extraction and Fusion for Audio-Visual Speech Recognition

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Evaluation of Different Feature Extraction Techniques for Continuous Speech Recognition

Extracting human's voice feature is the most important process in any speech recognition system. There are many feature extraction techniques which are already used such as MFCC, LPC and ZCPA; but still have some problems especially in the continuous speech. It is important to evaluate different feature extraction techniques for continuous speech by making a comparison between these techniques ...

Feature Extraction Techniques for Speech Recognition

Comparison of Different Speech Feature Extraction Techniques with and without Wavelet Transform to Kannada Speech Recognition

Pre-processing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. This paper deals with different speech processing techniques and the recognition accuracy with respect to wavelet transforms. It is shown that by applying wavelet transform to the conventional methods the signal recognition accuracy will be increased b...

Speech Recognition in Noisy Environment Using Different Feature Extraction Techniques

In this paper, different feature extraction methods for speech recognition system such as Melfrequency cepstral coefficients (MFCC), linear predictive coefficient cepstrum (LPCC) and Bark frequency cepstral coefficients (BFCC) are implemented and the comparison is done based on average recognition accuracy. We suggest a noise robust isolated word speech recognition system which can be applied i...