Speech Recognizer with Dynamic Alternative Path Search and Its Performance Evaluation

  • Tsuyoshi MorimotoEmail author
  • Shin-Ya Takahashi
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 52)


For a middle-size (around 1,000 words) vocabulary speech recognition, a Finite State Automaton (FSA) language model is widely used. However, defining a FSA model with sufficient coverage and consistency requires much human effort. We already proposed a method to automatically construct a FSA language model from learning corpus by use of FSA DP matching algorithm. Experiment results show that this model attains quite high recognition correct rate for closed data, but only low rate for open data. This is mainly because a necessary path does not appear in a generated FSA. To cope with this problem, we propose a new search algorithm that allows to jump dynamically to an alternative path when speech recognition of some words seems to fail. We report experiment results and discuss the effectiveness of the algorithm.


FSA language model Automatic construction of a language model Dynamic alternative path search Speech recognition performance 


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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Electronics and Computer Science DepartmentFukuoka UniversityFukuokaJapan

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