Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC

@inproceedings{Singh2011VectorQA,
  title={Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC},
  author={Satyanand Singh},
  year={2011}
}
Front-end or feature extractor is the first component in an automatic speaker recognition system. Feature extraction transforms the raw speech signal into a compact but effective representation that is more stable and discriminative than the original signal. Since the front-end is the first component in the chain, the quality of the later components (speaker modeling and pattern matching) is strongly determined by the quality of the front-end. In other words, classification can be at most as… CONTINUE READING
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A Vector Quantization approach Using MFCC for Speaker Recognition, International conference Systemic

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