Text to Phoneme Conversion in Persian Using Neural Networks
عنوان مقاله: Text to Phoneme Conversion in Persian Using Neural Networks
شناسه ملی مقاله: ACCSI09_040
منتشر شده در نهمین کنفرانس سالانه انجمن کامپیوتر ایران در سال 1382
شناسه ملی مقاله: ACCSI09_040
منتشر شده در نهمین کنفرانس سالانه انجمن کامپیوتر ایران در سال 1382
مشخصات نویسندگان مقاله:
Ghayooru - Electrical and Computer Engineering Isfahan University of Technology
Hendessi - Electrical and Computer Engineering Isfahan University of Technology
خلاصه مقاله:
Ghayooru - Electrical and Computer Engineering Isfahan University of Technology
Hendessi - Electrical and Computer Engineering Isfahan University of Technology
Speech is the most natural and widespread from of human communication. That’s why speech synthesis has interested researchers for decades. In this paper, a Persian text to speech system is presented. The system uses speech waveform concatenation method that is comparatively mature in text – to – speech synthesis. This paper discusses the experimental study on the use of neural network in text – to – speech systems for Persian language. In the context of text to phoneme conversion, the neural network demonstrate good performance. It is shown that a network can capture significant portion of regularities in the Persian pronunciation as well as absorb many of the irregularities .
کلمات کلیدی: Text to Speech , Neural Networks , Phoneme , HMM
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/45751/