HMM 기반 한국어 음성합성에서 지속시간 제어를 통한 자연성 개선 [韩语论文]

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Nowadays a corpus-based unit concatenation text-to-speech (TTS) system has been widely used because of its high quality synthesized speech. The high quality synthesized speech in a corpus-based TTS is obtained by using a large amount of speech DB in i...

Nowadays a corpus-based unit concatenation text-to-speech (TTS) system has been widely used because of its high quality synthesized speech. The high quality synthesized speech in a corpus-based TTS is obtained by using a large amount of speech DB in implementing the system. However, it is a difficult job and costs very much to collect a phonetically balanced large amount of speech DB, and segment to extract synthetic units having various voice characteristics. Thus, it is generally used for the serve based TTS system and is hard to be applied to the embedded system such as mobile devices having the limitation of the memory size. On the other hand, an HMM-based text-to-speech system (HTS) has recently drawn much attention to overcome such a problem. The HTS uses the statistical model, hidden Markov model (HMM) as a synthetic unit, to represent the spectra and prosodic characteristics of the speech signal. Thus the synthesis engine needs less memory and low computation complexity and is suitable for the embedded system. It also has the advantage that voice characteristics of the synthetic speech can be modified easily by transforming HMM parameters appropriately.
In this thesis, we implemented an HMM-based Korean text-to-speech system using a small sized Korean speech DB. We used the HTS software released on the school of Nagoya University with some amount of SeoulMal DB, and got phoneme labeling information using a HTK. The synthetic speech has shown very intelligible vocoded speech quality though naturalness was not enough. This is because, we think, feature parameters were not modeled well in the HMM training procedure due to the limited speech DB. Thus we proposed a method to increase the naturalness of the synthetic speech by controlling of duration model parameters in HMM-based Korean text-to speech system. We performed a paired comparison test to verify that theses techniques are effective. The test result with the preference scores of 73.8% has shown the improvement of the naturalness of the synthetic speech through controlling the duration model parameters.

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