Abstract
Speech/non-speech (S/NS) detection plays the important role for automatic speech recognition (ASR) system, especially in the case of isolated words or commands recognition. Even in continuous speech a S/NS decision can be made at the beginning and at the end of a sequence resulting in a “sleep mode” of the speech recognizer during the silence and in a reduction of computation demands. It is very difficult, however, to precisely locate the endpoints of the input utterance because of unpredictable background noise. In the proposed method in this paper, we make use of the advantages of two approaches (i.e. to try to find the best set of heuristic features and apply a statistical induction method) for the best S/NS decision.
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References
Yang, C-H., Hsieh, M-S.: Robust Endpoint Detection for In-Car Speech Recognition, ICSLP 2000, Beijing, Paper Number 251.
Zhu, J., Chen, F.: The Analysis and application of a New Endpoint Detection Method Base on Distance of Autocorrelated Similarity, ESCA, EuroSpeech’ 99, Budapest, Hungary. ISSN 1018-4074, pp. 105–108.
Karray, L., Monné, J.: Robust Speech/non-speech Detection in Adverse Conditions Based on Noise and Speech Statistics, ICSLP’ 98, Sydney, Paper Number 430.
Tessama, T.: New Methods for the Detection of Voiced, Unvoiced, Silent, Transition Regions in Speech Signals, Advances in Modelling & Analysis, B, AMSE Press (France), Vol. 31, No. 3, 1994, pp. 1–10, 1993.
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Prcín, M., Müller, L. (2002). Heuristic and Statistical Methods for Speech/Non-speech Detector Design. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2002. Lecture Notes in Computer Science(), vol 2448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46154-X_42
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DOI: https://doi.org/10.1007/3-540-46154-X_42
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