• 대한음성학회지:말소리
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• 제43호
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• pp.89-99
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• 2002

Recently, researches into ways of improving large vocabulary continuous speech recognition and speech synthesis are being carried out intensively as the field of speech information technology is progressing rapidly. In the field of speech recognition, developments of stochastic methods such as HMM require large amount of speech data for training, and also in the field of speech synthesis, recent practices show that synthesis of better quality can be produced by selecting and connecting only the variable size of speech data from the large amount of speech data. In this paper we design and discuss linguistic contents for speech copora for speech recognition and synthesis to be shared in common.

• ETRI Journal
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• 제31권4호
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• pp.457-459
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• 2009

The optimum maximum voiced frequency (MVF) estimation-based two-band excitation for hidden Markov model-based speech synthesis is presented. An analysis-by-synthesis scheme is adopted for the MVF estimation which leads to the minimum spectral distortion of synthesized speech. Experimental results show that the proposed method significantly improves synthetic speech quality.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 제15회 음성통신 및 신호처리 워크샵(KSCSP 98 15권1호)
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• pp.356-359
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• 1998

This paper proposes the speech synthesis method using Korean prosodic rules as an important technique for Korean speech synthesis. The prosodic model for speech synthesis is composed of accentual phrases and intonational phrases which are derived from hierarchical structure of prosody. This prosodic model controls duration time, intonation and pause of synthesized speech. Synthesis units constitute of demi-syllables and VCV-triphones which can make unlimited vocabularies, and TD-PSOLA is used a sthe synthesis method.

• The Journal of the Acoustical Society of Korea
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• 제20권4E호
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• pp.31-38
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• 2001

A large-scale synthesis database for a unit selection based synthesis method usually retains redundant synthesis unit instances, which are useless to the synthetic speech quality. In this paper, to eliminate those instances from the synthesis database, we proposed a new pruning method called weighted vector quantization (WVQ). The WVQ reflects relative importance of each synthesis unit instance when clustering the similar instances using vector quantization (VQ) technique. The proposed method was compared with two conventional pruning methods through the objective and subjective evaluations of the synthetic speech quality: one to simply limit maximum number of instance, and the other based on normal VQ-based clustering. The proposed method showed the best performance under 50% reduction rates. Over 50% of reduction rates, the synthetic speech quality is not seriously but perceptibly degraded. Using the proposed method, the synthesis database can be efficiently reduced without serious degradation of the synthetic speech quality.

• 음성과학
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• 제1권
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• pp.295-314
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• 1997

In this study, we will implement a flexible formant analysis and synthesis system. In the analysis part, the two-channel (i.e., speech & EGG signals) approach is investigated for accurate estimation of formant information. The EGG signal is used for extracting exact pitch information that is needed for the pitch synchronous LPC analysis and closed phase LPC analysis. In the synthesis part, Klatt formant synthesizer is modified so that the user can change synthesis parameters arbitarily. Experimental results demonstrate the superiority of the two-channel analysis method over the one-channel(speech signal only) method in analysis as well as in synthesis. The implemented system is expected to be very helpful for studing the effects of synthesis parameters on the quality of synthetic speech and for the development of Korean text-to-speech(TTS) system with the formant synthesis method.

• 음성과학
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• 제9권1호
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• pp.207-215
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• 2002

Perceptual evaluation of duration models of spoken Korean was carried out based on the Classification and Regression Tree (CART) model for text-to-speech conversion. A reference set of durations was produced by a commercial text-to-speech synthesis system for comparison. The duration model which was built in the previous research (Chung & Huckvale, 2001) was applied to a Korean language speech synthesis diphone database, 'Hanmal (HN 1.0)'. The synthetic speech produced by the CART duration model was preferred in the subjective preference test by a small margin and the synthetic speech from the commercial system was superior in the clarity test. In the course of preparing the experiment, a labeled database of spoken Korean with 670 sentences was constructed. As a result of the experiment, a trained duration model for speech synthesis was obtained. The 'Hanmal' diphone database for Korean speech synthesis was also developed as a by-product of the perceptual evaluation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.338-338
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• 2000

This paper proposes a modified TD-PSOLA algorithm for Korean speech synthesis. A WSS (Weighted score search) algorithm is proposed for pitch detection and speech synthesis engine is designed using 46 phones database.

• 한국음향학회지
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• 제18권7호
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• pp.10-16
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• 1999

본 논문에서는 설계하지 않은 연속 음성 코퍼스로부터 추출된 CVC 음성 세그먼트를 사용하는 연결 기반 음성 합성기를 제안한다. 연속 음성은 각 음운간의 상호조음효과가 비교적 잘 반영되고, 자연스러운 억양 변화를 포함하고 있으므로 이를 적절하게 활용할 수 있는 합성 단위를 선택하면 자연스런 음성합성이 가능하다. 여러 가지 합성단위 가운데 CVC 합성 단위는 자음의 안정 부분에서 접속이 일어나므로 연결부에서의 음질 저하가 적고, 전후 자음과 모음간의 조음 현상을 잘 반영하는 장점이 있다. 본 논문에서는 CVC 합성 단위를 사용하는 경우 나타나는 문장 세그먼트들의 조합을 4가지로 분류하여 각각의 통계적 특성과 합성음성의 품질을 분석하고, CVC에 근거한 새로운 복합 합성 단위를 사용하는 방식을 제안한다. 제안된 방식을 사용하여 설계하지 않은 연속 음성 코퍼스로부터 CVC 음성 세그먼트를 추출하여 다양한 예제 문장을 합성하였다. 만일 필요한 CVC 음성 세그먼트가 음성 코퍼스에 존재하지 않는 경우 반음절 음성 세그먼트로 대치하여 합성하였다. 실험 결과 약 100 Mbytes의 연속 음성 코퍼스로 비교적 자연스러운 음성합성이 가능함을 알 수 있었다.

• 말소리와 음성과학
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• 제9권1호
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• pp.41-47
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• 2017

The main advantage of the statistical parametric speech synthesis is its flexibility in changing voice characteristics. A personalized text-to-speech(TTS) system can be implemented by combining a speech synthesis system and a voice transformation system, and it is widely used in many application areas. It is known that the fundamental frequency and the spectral envelope of speech signal can be independently modified to convert the voice characteristics. Also it is important to maintain naturalness of the transformed speech. In this paper, a speech synthesis system based on Hidden Markov Model(HMM-based speech synthesis, HTS) using the STRAIGHT vocoder is constructed and voice transformation is conducted by modifying the fundamental frequency and spectral envelope. The fundamental frequency is transformed in a scaling method, and the spectral envelope is transformed through frequency warping method to control the speaker's vocal tract length. In particular, this study proposes a voice transformation method using the correlation between fundamental frequency and vocal tract length. Subjective evaluations were conducted to assess preference and mean opinion scores(MOS) for naturalness of synthetic speech. Experimental results showed that the proposed voice transformation method achieved higher preference than baseline systems while maintaining the naturalness of the speech quality.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.949-956
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• 1994

In this paper, we introduce a new speech synthesis method for Japanese and Korean arbitrary sentences using the natural speech data-base. Also, application of this method to a CAI system is discussed. In our synthesis method, a basic sentence and basic accent-phrases are selected from the data-base against a target sentence. Factors for those selections are phrase dependency structure (separation degree), number of morae, type of accent and phonemic labels. The target pitch pattern and phonemic parameter series are generated using those selected basic units. As the pitch pattern is generated using patterns which are directly extracted form real speech, it is expected to be more natural than any other pattern which is estimated by any model. Until now, we have examined this method on Japanese sentence speech and affirmed that the synthetic sound preserves human-like features fairly well. Now we extend this method to Korean sentence speech synthesis. Further more, we are trying to apply this synthesis unit to a CAI system.