A Recognition Judgment Method of Isolated-Word Speech-Recognition

Isolated-word speech-recognition system adopted the shortest distance of Dynamic Time Warping (DTW) to make recognition judgment, which has the disadvantage of high False Accept Rate (FAR), poor anti-noise and robustness. This paper proposes a new method based on DTW distance Threshold Estimation for recognition judgment. This method processes the maximum distance between template speech and training input speech multiplying adjusting coefficient, then plus noise DTW distance, which regard the final result as distance Threshold Estimation. At the time of doing speech recognition, if the distance between testing speech and template speech exceeds the Threshold Estimation, then the system will not recognize this speech. The experiment shows that this method can greatly improve the anti-noise and robustness performance of the Isolated-word speech-recognition system and solve the problem of high FAR.

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HMM Based Enhanced Dynamic Time Warping Model for Efficient Hindi Language Speech Recognition System

Mobile Communication and Power Engineering - Communications in Computer and Information Science ◽

10.1007/978-3-642-35864-7_28 ◽

2013 ◽

pp. 200-206

Author(s):

Sharma Krishna Kumar ◽

Lavania Krishan Kant ◽

Sharma Shachi

Keyword(s):

Speech Recognition ◽

Dynamic Time Warping ◽

Recognition System ◽

Speech Recognition System ◽

Time Warping ◽

Hindi Language ◽

Dynamic Time

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An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

Mathematical Problems in Engineering ◽

10.1155/2014/898729 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Ing-Jr Ding ◽

Yen-Ming Hsu

Keyword(s):

Speech Recognition ◽

Automatic Speech Recognition ◽

Template Matching ◽

Dynamic Time Warping ◽

Recognition System ◽

Home Automation ◽

Speech Recognition System ◽

Time Warping ◽

Feature Based ◽

Dynamic Time

In the past, the kernel of automatic speech recognition (ASR) is dynamic time warping (DTW), which is feature-based template matching and belongs to the category technique of dynamic programming (DP). Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM-) like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation). A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

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