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Detection-Based Decoder

  • Qi (Peter) LiEmail author
Chapter
  • 649 Downloads
Part of the Signals and Communication Technology book series (SCT)

Abstract

Decoding or searching is an important task in both speaker and speech recognition. In speaker verification (SV), given a spoken password and a speakerdependent hidden Markov model (HMM), the task of decoding or searching is to find optimal state alignments in the sense of maximum likelihood score of the entire utterance. Currently, the most popular decoding algorithm is the Viterbi algorithm with a pre-defined beam width to reduce the search space; however, it is difficult to determine a suitable beam width beforehand. A small beam width may miss the optimal path while a large one may slow down the process. To address the problem, the author has developed a non-heuristic algorithm to reduce the search space. The details are presented in this chapter.

Keywords

Hide Markov Model Automatic Speech Recognition Speaker Recognition Viterbi Algorithm Sequential Probability Ratio Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg  2012

Authors and Affiliations

  1. 1.Li Creative Technologies (LcT), IncFlorham ParkUSA

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