• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.161-169
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• 2012

This paper presents a robust speech end-point detector using double talk detection in echoic conditioned speech recognition robot. The proposed method consists of combining conventional end-point detector result and double talk detector result. We have tested the proposed method in isolated word recognition system under echoic conditioned environment. As a result, the proposed algorithm shows superior performance of 30 % to the available techniques in the points of speech recognition rates.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.183-186
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• 2002

The speech detection is one of the important problems in real-time speech recognition. The accurate detection of speech boundaries is crucial to the performance of speech recognizer. In this paper, we propose a speech detector based on Mel-band selection through training. In order to show the excellence of the proposed algorithm, we compare it with a conventional one, so called, EPD-VAA (EndPoint Detector based on Voice Activity Detection). The proposed speech detector is trained in order to better extract keyword speech than other speech. EPD-VAA usually works well in high SNR but it doesn't work well any more in low SNR. But the proposed algorithm pre-selects useful bands through keyword training and decides the speech boundary according to the energy level of the sub-bands that is previously selected. The experimental result shows that the proposed algorithm outperforms the EPD-VAA.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.187-190
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• 2000

In this paper, implementation of speech Recognizer system, Separated from Personal computer. By using DSP, this intends to extend the voice recognizing, limited into PC because of amount of data and calculations. For this performance The thesis uses the real time End point detector and organizes no additional device between human and the system, characteristic vector are that detects End point and voice from absolute energy and ZCR, that uses 12 difference Cepstrum from LPC, that uses the method to compensate the process of pattern separating and pre-calculated standard pattern limitation.