• Title/Summary/Keyword: MRTCN

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Performance Improvement of Connected Digit Recognition with Channel Compensation Method for Telephone speech (채널보상기법을 사용한 전화 음성 연속숫자음의 인식 성능향상)

  • Kim Min Sung;Jung Sung Yun;Son Jong Mok;Bae Keun Sung
    • MALSORI
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    • no.44
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    • pp.73-82
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    • 2002
  • Channel distortion degrades the performance of speech recognizer in telephone environment. It mainly results from the bandwidth limitation and variation of transmission channel. Variation of channel characteristics is usually represented as baseline shift in the cepstrum domain. Thus undesirable effect of the channel variation can be removed by subtracting the mean from the cepstrum. In this paper, to improve the recognition performance of Korea connected digit telephone speech, channel compensation methods such as CMN (Cepstral Mean Normalization), RTCN (Real Time Cepatral Normalization), MCMN (Modified CMN) and MRTCN (Modified RTCN) are applied to the static MFCC. Both MCMN and MRTCN are obtained from the CMN and RTCN, respectively, using variance normalization in the cepstrum domain. Using HTK v3.1 system, recognition experiments are performed for Korean connected digit telephone speech database released by SITEC (Speech Information Technology & Industry Promotion Center). Experiments have shown that MRTCN gives the best result with recognition rate of 90.11% for connected digit. This corresponds to the performance improvement over MFCC alone by 1.72%, i.e, error reduction rate of 14.82%.

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Analysis of Error Patterns in ]Korean Connected Digit Telephone Speech Recognition (한국어 연속 숫자음 전화 음성 인식에서의 오인식 유형 분석)

  • Kim Min Sung;Jung Sung Yun;Son Jong Mok;Bae Keun Sung;Kim Sang Hun
    • MALSORI
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    • no.46
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    • pp.77-86
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    • 2003
  • Channel distortion and coarticulation effect in the Korean connected digit telephone speech make it difficult to achieve high performance of connected digit recognition in the telephone environment. In this paper, as a basic research to improve the recognition performance of Korean connected digit telephone speech, recognition error patterns are investigated and analyzed. Korean connected digit telephone speech database released by SiTEC and HTK system are used for recognition experiments. Both DWFBA and MRTCN methods are used for feature extraction and channel compensation, respectively. Experimental results are discussed with our findings.

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Performance Comparison of Korean Connected Digit Telephone Speech Recognition According to Aurora Feature Extraction (Aurora 특징파라미터 추출기법에 따른 한국어 연속숫자음 전화음성의 인식 성능 비교)

  • Kim Min Sung;Jung Sung Yun;Son Jong Mok;Bae Keun Sung;Kim Sang Hun
    • Proceedings of the KSPS conference
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    • 2003.10a
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    • pp.145-148
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    • 2003
  • To improve the recognition performance of Korean connected digit telephone speech, in this paper, both Aurora feature extraction method that employs noise reduction 2-state Wiener filter and DWFBA method are investigated and used. CMN and MRTCN are applied to static features for channel compensation. Telephone digit speech database released by SITEC is used for recognition experiments with HTK system. Experimental results has shown that Aurora feature is slightly better than MFCC and DWFBA without channel compensation. And when channel compensation is included, Aurora feature is slightly better than DWFBA with MRTCN.

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Analysis of Error Patterns in Korean Connected Digit Telephone Speech Recognition (연결숫자음 전화음성 인식에서의 오인식 유형 분석)

  • Kim Min Sung;Jung Sung Yun;Son Jong Mok;Bae Keun Sung;Kim Sang Hun
    • Proceedings of the KSPS conference
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    • 2003.05a
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    • pp.115-118
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    • 2003
  • Channel distortion and coarticulation effect in the connected digit telephone speech make it difficult to recognize, and degrade recognition performance in the telephone environment. In this paper, as a basic research to improve the recognition performance of Korean connected digit telephone, error patterns are investigated and analyzed. Telephone digit speech database released by SITEC with HTK system is used for recognition experiments. Both DWFBA and MRTCN methods are used for feature extraction and channel compensation, respectively. Experimental results are discussed with our findings.

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