Developing HMM-Based Recognizers with ESMERALDA

  • Authors:
  • Gernot A. Fink

  • Affiliations:
  • -

  • Venue:
  • TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
  • Year:
  • 1999

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Abstract

ESMERALDA is an integrated environment for the development of speech recognition systems. It provides a powerful selection of methods for building statistical models together with an efficient incremental recognizer. In this paper the approaches adopted for estimating mixture densities, Hidden Markov Models, and n-gram language models are described as well as the algorithms applied during recognition. Evaluation results on a speaker independent spontaneous speech recognition task demonstrate the capabilities of ESMERALDA.