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Abstract
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Article Information:
Statistical Parametric Speech Synthesis of Malay Language using Found Training Data
Lau Chee Yong and Tan Tian Swee
Corresponding Author: Tan Tian Swee
Submitted: January 28, 2014
Accepted: February 10, 2014
Published: June 25, 2014 |
Abstract:
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The preparation of training data for statistical parametric speech synthesis can be sophisticated. To ensure the good quality of synthetic speech, high quality low noise recording must be prepared. The preparation of recording script can be also tremendous from words collection, words selection and sentences design. It requires tremendous human effort and takes a lot of time. In this study, we used alternative free source of recording and text such as audio-book, clean speech and so on as the training data. Some of the free source can provide high quality recording with low noise which is suitable to become training data. Statistical parametric speech synthesis method applying Hidden Markov Model (HMM) has been used. To test the reliability of synthetic speech, perceptual test has been conducted. The result of naturalness test is fairly reasonable. The intelligibility test showed encouraging result. The Word Error Rate (WER) for normal synthetic sentences is below 15% while for Semantically Unpredictable Sentences (SUS) is averagely in 30%. In short, using free and ready source as training data can leverage the process of preparing training data while obtaining motivating synthetic result.
Key words: Hidden Markov Model (HMM), letter to sound rule, statistical parametric speech synthesis, , , ,
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Cite this Reference:
Lau Chee Yong and Tan Tian Swee, . Statistical Parametric Speech Synthesis of Malay Language using Found Training Data. Research Journal of Applied Sciences, Engineering and Technology, (24): 5143-5147.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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