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International Journal of Information and Communication Technology Research (IJICT، جلد ۸، شماره ۲، صفحات ۳۳-۴۴
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Hybrid of Evolutionary and Swarm Intelligence Algorithms for Prosody Modeling in Natural Speech Synthesis |
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| چکیده انگلیسی مقاله |
To reduce the number of input features to a prosody generator in natural speech synthesis application, a hybrid of an evolutionary algorithm and a swarm intelligence-based algorithm is used for feature selection (FS) in this study. The input features to FS unit are word-level and syllable-level linguistic features. The word-level features include punctuation information, part-of-speech tags, semantic indicators, and length of the words. The syllable-level features include the phonemic structure and position indicator of the current syllable in a word. A modified Elman-type dynamic neural network (DNN) is used for prosody generation in this study. The output layer of this DNN provides prosody information at the syllable-level including pitch contour, log-energy level, duration information, and pause data. Simulation results show that the prosody information is predicted with an acceptable error by this hybrid soft-computing method as compared to Elman-type neural network prosody generator and binary gravitational search algorithm-based FS unit. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
| Mansour Sheikhan
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| نشانی اینترنتی |
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-47&slc_lang=fa&sid=1 |
| فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/417/article-417-1212350.pdf |
| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
fa |
| موضوعات مقاله منتشر شده |
فناوری اطلاعات |
| نوع مقاله منتشر شده |
پژوهشی |
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