Using posterior-based features in template matching for speech recognition

  title={Using posterior-based features in template matching for speech recognition},
  author={Guillermo Aradilla and Jithendra Vepa and Herv{\'e} Bourlard},
Given the availability of large speech corpora, as well as the increasing of memory and computational resources, the use of template matching approaches for automatic speech recognition (ASR) have recently attracted new attention. In such template-based approaches, speech is typically represented in terms of acoustic vector sequences, using spectral-based features such as MFCC of PLP, and local distances are usually based on Euclidean or Mahalanobis distances. In the present paper, we further… CONTINUE READING
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