Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/37807
標題: An efficient Mandarin text-to-speech system on time domain
作者: Lin, Y.J.
余明興
Yu, M.S.
關鍵字: text-to-speech
intelligibility
comprehensibility
naturalness
synthesizer
期刊/報告no:: Ieice Transactions on Information and Systems, Volume E81D, Issue 6, Page(s) 545-555.
摘要: This paper describes a complete Mandarin text-to-speech system on time domain. We take advantage of the advancement of memory technology, which achieves ever-increasing capacity and ever-lower price. We try to collect as more as possi ble the synthesis units in a Mandarin text-to-speech system. With such an effort, we developed simpler speech processing techniques and achieved faster processing speed by using only an ordinary personal computer. We also developed delicate methods to measure the intelligibility, comprehensibility, and naturalness of a Mandarin text-to-speech system. Our system performs very well compared with existing systems. We first develop a set of useful algorithms and methods to deal with some features of the syllables, such as duration, amplitude, fundamental frequency, pause, and so on. Based on these algorithms and methods, we then build a Mandarin text-to-speech system. Given any Chinese text in some computerized form, e.g., in BIG-5 code representation, our system can pronounce the text in real time. Our text-to-speech system runs on an IBM 80486 compatible PC, with no special hardware for signal processing. The evaluation of our text-to-speech system is based on a proposed subjective evaluation method. An evaluation was made by 51 undergraduate students. The intelligibility of our text-to-speech system is 99.5%, the comprehensibility of our text-to-speech system is 92.6%, and the naturalness of our text-to-speech system is 81.512 points in a percentile grading system (the highest score is 100 points, and the lowest score is 0 point). Other 40 Ph.D. students also did the same evaluation about naturalness. The result shows that the naturalness of our text-to-speech system is 82.8 points in a percentile grading system.
URI: http://hdl.handle.net/11455/37807
ISSN: 0916-8532
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