• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.33-36
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• 1999

본 논문에서는 기존의 text-to-speech(TTS) 합성방식이 미리 정해진 화자에 의한 단조로운 합성음을 가지는 문제를 극복하기 위하여, 임의의 화자의 음색을 표현할 수 있는 화자 변환(Voice Conversion) 기능을 구현하였다. 구현된 방식은 화자의 음향공간을 Gaussian Mixture Model(GMM)로 모델링하여 연속 확률 분포에 따른 화자 변환을 가능케 했다. 원시화자(source)와 목적화자(target)간의 특징 벡터의 joint density function을 이용하여 목적화자의 음향공간 특징벡터와 변환된 벡터간의 제곱오류를 최소화하는 변환 함수를 구하였으며, 구해진 변환 함수로 벡터 mapping에 의한 스펙트럼 포락선을 변환했다. 운율 변환은 음성 신호를 정현파 모델에 의해서 모델링하고, 분석된 운율 정보(피치, 지속 시간)는 평균값을 고려해서 변환했다. 성능 평가를 위해서 VQ mapping 방법을 함께 구현하여 각각의 정규화된 켑스트럼 거리를 구해서 성능을 비교 평가하였다. 합성시에는 ABS-OLA 기반의 정현파 모델링 방식을 채택함으로써 자연스러운 합성음을 생성할 수 있었다.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.191-195
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• 1999

자연스럽고 명료한 한국어 Text-to-Speech 변환 시스템을 위해서 음소의 지속 시간을 제어하는 일은 매우 중요하다. 음소의 지속 시간은 여러 가지 문맥 정보에 의해서 변화하므로 제어 규칙에 의존하기 보다 방대한 데이터베이스를 이용하여 통계적인 기법으로 음소의 지속 시간에 변화를 주는 요인을 찾아내려고 하는 것이 지금의 추세이다. 본 연구에서도 트리기반 모델링 방법중의 하나인 CART(classification and regression tree) 방법을 사용하여 회귀 트리를 생성하고, 생성된 트리에 기반하여 음소의 지속 시간 예측 모델과, 자연스러운 끊어 읽기를 위한 휴지 기간 예측 모델을 제안하고 있다. 실험에 사용한 음성코퍼스는 550개의 문장으로 구성되어 있으며, 이 중 428개 문장으로 회귀 트리를 학습시켰고, 나머지 122개의 문장으로 실험하였다. 모델의 평가를 위해서 실제값과 예측값과의 상관관계를 구하였더니 음소의 지속 시간을 예측하는 회귀 트리에서는 상관계수가 0.84로 계산되었고, 끊어 읽는 경계에서의 휴지 기간을 예측하는 회귀 트리에서는 상관계수가 0.63으로 나타났다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.526-527
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• 2023

Speech emotion recognition(SER) is one of the interesting topics in the machine learning field. By developing multi-modal speech emotion recognition system, we can get numerous benefits. This paper explain about fusing BERT as the text recognizer and CNN as the speech recognizer to built a multi-modal SER system.

• Speech Sciences
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• v.1
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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.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.209-215
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• 2010

Recently portable terminal is received attention by wireless networks and mass capacity ROM. In this result, TTS(Text to Speech) system is inserted to portable terminal. Nevertheless high quality synthesis is difficult in portable terminal, users need high quality synthesis. In this paper, we proposed Distributed TTS (DTTS) that was composed of server and terminal. The DTTS on corpus based speech synthesis can be high quality synthesis. Synthesis system in server that generate optimized speech concatenation information after database search and transmit terminal. Synthesis system in terminal make high quality speech synthesis as low computation using transmitted speech concatenation information from server. The proposed method that can be reducing complexity, smaller power consumption and efficient maintenance.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2431-2434
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• 2003

In this research, our goal is to realize Korean Distribute TTS system with server/client function in wireless network. The speech databases and some routines of TTS system is stuck with the server which has strong functions and we made Korean speech databases and accomplished research about DB which is suitable for distributed TTS. We designed a terminal has the minimum setting which operate this TTS and designed proper protocol so we will check action of Distributed TTS.

• Phonetics and Speech Sciences
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• v.9 no.1
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1042-1045
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• 2003

In this paper, we propose the speaker identification system that uses vowel that has speaker's characteristic. System is divided to speech feature extraction part and speaker identification part. Speech feature extraction part extracts speaker's feature. Voiced speech has the characteristic that divides speakers. For vowel extraction, formants are used in voiced speech through frequency analysis. Vowel-a that different formants is extracted in text. Pitch, formant, intensity, log area ratio, LP coefficients, cepstral coefficients are used by method to draw characteristic. The cpestral coefficients that show the best performance in speaker identification among several methods are used. Speaker identification part distinguishes speaker using Neural Network. 12 order cepstral coefficients are used learning input data. Neural Network's structure is MLP and learning algorithm is BP (Backpropagation). Hidden nodes and output nodes are incremented. The nodes in the incremental learning neural network are interconnected via weighted links and each node in a layer is generally connected to each node in the succeeding layer leaving the output node to provide output for the network. Though the vowel extract and incremental learning, the proposed system uses low learning data and reduces learning time and improves identification rate.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.369-372
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• 2002

In this paper, we present an improved TTS synthesis system using articulatory synthesis and concatenative synthesis. In concatenative synthesis, segments of speech are excised from spoken utterances and connected to form the desired speech signal. We adopt LPC as a parameter, VQ to reduce the memory capacity, and TD-PSOLA to solve the naturalness problem.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.233-242
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• 2003

A TTS(Text-To-Speech) System is a computer-based system that should be able to read any text aloud. To output a natural voice, we need a general knowledge of language, a lot of time, and effort. Furthermore, the sound pattern of english has a variable pattern, which consists of phonemic and morphological analysis. It is very difficult to maintain consistency of pattern. To handle these problems, we present a system based on phonemic analysis for vowel and consonant. By analyzing phonological variations frequently found in spoken english, we have derived about phonemic contexts that would trigger the multilevel application of the corresponding phonological process, which consists of phonemic and allophonic rules. In conclusion, we have a rule data which consists of phoneme, and a engine which economize in system. The proposed system can use not only communication system, but also utilize office automation and so on.