Using output probability distribution for improving speech recognition in adverse environment

Shilei Huang; Xiang Xie; Jingming Kuang

Using output probability distribution for improving speech recognition in adverse environment

Shilei Huang^*, Xiang Xie, Jingming Kuang

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper proposed a method to improve the accuracy of small vocabulary isolated word speaker-independent speech recognition in adverse environment. The proposed approach is implemented by using Output Probability Distributions (OPDs) and Support Vector Machine (SVM). OPDs improve the system performance by modeling inter-word relationships; then SVM classifiers are used to discriminate the difference between OPD models. The system was tested using isolated Mandarin digits database, corrupted with the NOISEX-92 database. The experiments have achieved good result in noise conditions, the WER dropped about 30% on average when compared to the HMM recognizer.

Original language	English
Pages	929-932
Number of pages	4
Publication status	Published - 2005
Event	9th European Conference on Speech Communication and Technology - Lisbon, Portugal Duration: 4 Sept 2005 → 8 Sept 2005

Conference

Conference	9th European Conference on Speech Communication and Technology
Country/Territory	Portugal
City	Lisbon
Period	4/09/05 → 8/09/05

Cite this

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title = "Using output probability distribution for improving speech recognition in adverse environment",

abstract = "This paper proposed a method to improve the accuracy of small vocabulary isolated word speaker-independent speech recognition in adverse environment. The proposed approach is implemented by using Output Probability Distributions (OPDs) and Support Vector Machine (SVM). OPDs improve the system performance by modeling inter-word relationships; then SVM classifiers are used to discriminate the difference between OPD models. The system was tested using isolated Mandarin digits database, corrupted with the NOISEX-92 database. The experiments have achieved good result in noise conditions, the WER dropped about 30% on average when compared to the HMM recognizer.",

author = "Shilei Huang and Xiang Xie and Jingming Kuang",

year = "2005",

language = "English",

pages = "929--932",

note = "9th European Conference on Speech Communication and Technology ; Conference date: 04-09-2005 Through 08-09-2005",

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TY - CONF

T1 - Using output probability distribution for improving speech recognition in adverse environment

AU - Huang, Shilei

AU - Xie, Xiang

AU - Kuang, Jingming

PY - 2005

Y1 - 2005

N2 - This paper proposed a method to improve the accuracy of small vocabulary isolated word speaker-independent speech recognition in adverse environment. The proposed approach is implemented by using Output Probability Distributions (OPDs) and Support Vector Machine (SVM). OPDs improve the system performance by modeling inter-word relationships; then SVM classifiers are used to discriminate the difference between OPD models. The system was tested using isolated Mandarin digits database, corrupted with the NOISEX-92 database. The experiments have achieved good result in noise conditions, the WER dropped about 30% on average when compared to the HMM recognizer.

AB - This paper proposed a method to improve the accuracy of small vocabulary isolated word speaker-independent speech recognition in adverse environment. The proposed approach is implemented by using Output Probability Distributions (OPDs) and Support Vector Machine (SVM). OPDs improve the system performance by modeling inter-word relationships; then SVM classifiers are used to discriminate the difference between OPD models. The system was tested using isolated Mandarin digits database, corrupted with the NOISEX-92 database. The experiments have achieved good result in noise conditions, the WER dropped about 30% on average when compared to the HMM recognizer.

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M3 - Paper

AN - SCOPUS:33745192530

SP - 929

EP - 932

T2 - 9th European Conference on Speech Communication and Technology

Y2 - 4 September 2005 through 8 September 2005

ER -

Using output probability distribution for improving speech recognition in adverse environment

Abstract

Conference

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