Open Domain Continuous Filipino Speech Recognition: Challenges and Baseline Experiments

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概要

• 論文の詳細を見る

• In this paper, a new database suitable for HMM-based automatic Filipino speech recognition is described for the purpose of training a domain-independent, large-vocabulary continuous speech recognition system. Although it is known that high-performance speech recognition systems depend on a superior speech database used in the training stage, due to the lack of such an appropriate database, previous reports on Filipino speech recognition had to contend with serious data sparsity issues. In this paper we alleviate such sparsity through appropriate data analysis that makes the evaluation results more reliable. The best system is identified through its low word-error rate to a cross-validation set containing almost three hours of unknown speech data. Language-dependent problems are discussed, and their impact on accuracy was analyzed. The approach is currently data driven, however it serves as a competent baseline model for succeeding future developments.

• The Institute of Electronics, Information and Communication Engineersの論文

著者

• ANG Federico

  DSP Laboratory, University of the Philippines

• GUEVARA Rowena

  DSP Laboratory, University of the Philippines

• MIYANAGA Yoshikazu

  ICN Laboratory, Hokkaido University

• CAJOTE Rhandley

  DSP Laboratory, University of the Philippines

• ILAO Joel

  DSP Laboratory, University of the Philippines

• BAYONA Michael

  DSP Laboratory, University of the Philippines

• LAGUNA Ann

  DSP Laboratory, University of the Philippines

関連論文

• Open Domain Continuous Filipino Speech Recognition: Challenges and Baseline Experiments

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