A Discriminative Segmental Speech Model and Its Application to Hungarian Number Recognition

نویسندگان

  • László Tóth
  • András Kocsor
  • Kornél Kovács
چکیده

Abstract. This paper presents a stochastic segmental speech recognizer that models the a posteriori probabilities directly. The main issues concerning the system are segmental phoneme classification, utterance-level aggregation and the pruning of the search space. For phoneme classification artificial neural networks and support vector machines are applied. Phonemic segmentation and utterance-level aggregation is performed with the aid of anti-phoneme modeling. At the phoneme level the system convincingly outperforms the HMM system trained on the same corpus, while at the word level it attains the performance of the HMM system trained without embedded training.

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تاریخ انتشار 2000