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IDENTIFICATION AND VERIFICATION OF SPEAKER USING MEL

Viplav Gautam, Saurabh Sharma, Swapnil Gautam, Gaurav Sharma

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Abstract

Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. Feature extraction is the most important step for speaker recognition. In this work, the Mel Frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. MFCC is based on the human peripheral auditory System. Generally, MFCC for feature extraction is used to improve the efficiency of speaker recognition.

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What this paper is about

Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. Feature extraction is the most important step for speaker recognition. In this work, the Mel Frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. MFCC is based on the human peripheral auditory System. Generally, MFCC for feature extraction is used to improve the efficiency of speaker recognition.

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Available abstract

Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. Feature extraction is the most important step for speaker recognition. In this work, the Mel Frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. MFCC is based on the human peripheral auditory System. Generally, MFCC for feature extraction is used to improve the efficiency of speaker recognition.

Key concepts: Mel-frequency cepstrum, Speech recognition, Speaker recognition, Computer science, Feature extraction, Speaker diarisation, Cepstrum, Speech processing

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