Browsing by Author "Hwang, SH"

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A Mandarin text-to-speech system
(1996)
Hwang, SH
;
Chen, SH
;
Wang, YR
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交大名義發表
;
電信工程研究所
In this paper, the implementation of a high-performance Mandarin TTS system is presented. The system is composed of four main parts: text analysis (TA), prosodic information generation (PIG), waveform table (WT) of 411 base-syllables, and PSOLA-based waveform synthesis (PSOLA). In TA, a statistical model based method is first employed to automatically tag the input text to obtain the word sequence and the associated part-of-speech (POS) sequence. A lexicon containing about 80000 words is used in the tagging process. Then the corresponding base-syllable sequence is found and used to get from WT the basic wave-form sequence. Some linguistic features used in PIG are also extracted in TA, In PIG, a four-layer recurrent neural network (RNN) is employed to generate some prosodic information including pitch. contour, energy level, initial duration and final duration of syllable as well as inter-syllable pause duration. Finally, in PSOLA the basic waveform sequence is modified using the prosodic information to generate output synthetic speech, The whole system is implemented by software on a PC/AT 486 with a 16-bit Sound Blaster add-on card. Only 3.2 Mbyte memory space is required. It can synthesize speech in real-time for any input Chinese text. Informal listening tests by many native Chinese living in Taiwan confirmed that the synthetic speech sounded very fluent and natural.
An RNN-based prosodic information synthesizer for Mandarin text-to-speech
(1998-05-01)
Chen, SH
;
Hwang, SH
;
Wang, YR
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
A new RNN-based prosodic information synthesizer for Mandarin Chinese text-to-speech (TTS) is proposed in this paper. Its four-layer recurrent neural network (RNN) generates prosodic information such as syllable pitch contours, syllable energy levels, syllable initial and final durations, as well as inter-syllable pause durations. The input layer and first hidden layer operate with a word-synchronized clock to represent current-word phonologic states within the prosodic structure of text to be synthesized. The second hidden layer and output layer operate on a syllable-synchronized clock and use outputs from the preceding layers, along with additional syllable-level inputs fed directly to the second hidden layer, to generate desired prosodic parameters. The RNN was trained on a large set of actual utterances accompanied by associated texts, and can automatically learn many human-prosody phonologic rules, including the well-known Sandhi Tone 3 F0-change rule. Experimental results show that all synthesized prosodic parameter sequences matched quite well with their original counterparts, and a pitch-synchronous-overlap-add-based (PSOLA-based) Mandarin TTS system was also used for testing of our approach. While subjective tests are difficult to perform and remain to be done in the future, we have carried out informal listening tests by a significant number of native Chinese speakers and the results confirmed that all synthesized speech sounded quite natural.