• 제목/요약/키워드: prosody modeling

검색결과 8건 처리시간 0.024초

음성합성을 위한 C-ToBI기반의 중국어 운율 경계와 F0 contour 생성 (Chinese Prosody Generation Based on C-ToBI Representation for Text-to-Speech)

  • 김승원;정옥;이근배;김병창
    • 대한음성학회지:말소리
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    • 제53호
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    • pp.75-92
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    • 2005
  • Prosody Generation Based on C-ToBI Representation for Text-to-SpeechSeungwon Kim, Yu Zheng, Gary Geunbae Lee, Byeongchang KimProsody modeling is critical in developing text-to-speech (TTS) systems where speech synthesis is used to automatically generate natural speech. In this paper, we present a prosody generation architecture based on Chinese Tone and Break Index (C-ToBI) representation. ToBI is a multi-tier representation system based on linguistic knowledge to transcribe events in an utterance. The TTS system which adopts ToBI as an intermediate representation is known to exhibit higher flexibility, modularity and domain/task portability compared with the direct prosody generation TTS systems. However, the cost of corpus preparation is very expensive for practical-level performance because the ToBI labeled corpus has been manually constructed by many prosody experts and normally requires a large amount of data for accurate statistical prosody modeling. This paper proposes a new method which transcribes the C-ToBI labels automatically in Chinese speech. We model Chinese prosody generation as a classification problem and apply conditional Maximum Entropy (ME) classification to this problem. We empirically verify the usefulness of various natural language and phonology features to make well-integrated features for ME framework.

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PROSODY IN SPEECH TECHNOLOGY - National project and some of our related works -

  • Hirose Keikichi
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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    • pp.15-18
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    • 2002
  • Prosodic features of speech are known to play an important role in the transmission of linguistic information in human conversation. Their roles in the transmission of para- and non- linguistic information are even much more. In spite of their importance in human conversation, from engineering viewpoint, research focuses are mainly placed on segmental features, and not so much on prosodic features. With the aim of promoting research works on prosody, a research project 'Prosody and Speech Processing' is now going on. A rough sketch of the project is first given in the paper. Then, the paper introduces several prosody-related research works, which are going on in our laboratory. They include, corpus-based fundamental frequency contour generation, speech rate control for dialogue-like speech synthesis, analysis of prosodic features of emotional speech, reply speech generation in spoken dialogue systems, and language modeling with prosodic boundaries.

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자연어 처리 기반 한국어 TTS 시스템 구현 (Implementation of Korean TTS System based on Natural Language Processing)

  • 김병창;이근배
    • 대한음성학회지:말소리
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    • 제46호
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    • pp.51-64
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    • 2003
  • In order to produce high quality synthesized speech, it is very important to get an accurate grapheme-to-phoneme conversion and prosody model from texts using natural language processing. Robust preprocessing for non-Korean characters should also be required. In this paper, we analyzed Korean texts using a morphological analyzer, part-of-speech tagger and syntactic chunker. We present a new grapheme-to-phoneme conversion method for Korean using a hybrid method with a phonetic pattern dictionary and CCV (consonant vowel) LTS (letter to sound) rules, for unlimited vocabulary Korean TTS. We constructed a prosody model using a probabilistic method and decision tree-based method. The probabilistic method atone usually suffers from performance degradation due to inherent data sparseness problems. So we adopted tree-based error correction to overcome these training data limitations.

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한국어 음성합성기의 운율 예측을 위한 의사결정트리 모델에 관한 연구 (A Study of Decision Tree Modeling for Predicting the Prosody of Corpus-based Korean Text-To-Speech Synthesis)

  • 강선미;권오일
    • 음성과학
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    • 제14권2호
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    • pp.91-103
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    • 2007
  • The purpose of this paper is to develop a model enabling to predict the prosody of Korean text-to-speech synthesis using the CART and SKES algorithms. CART prefers a prediction variable in many instances. Therefore, a partition method by F-Test was applied to CART which had reduced the number of instances by grouping phonemes. Furthermore, the quality of the text-to-speech synthesis was evaluated after applying the SKES algorithm to the same data size. For the evaluation, MOS tests were performed on 30 men and women in their twenties. Results showed that the synthesized speech was improved in a more clear and natural manner by applying the SKES algorithm.

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한국어 대화체 TTS 개발을 위한 발음 및 운율 추정 (Grapheme-to-Phoneme Conversion and Prosody Modeling for Korean Conversational Style TTS)

  • 이진식;김승원;김병창;이근배
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 2006년도 추계학술대회 발표논문집
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    • pp.135-138
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    • 2006
  • In this paper, we introduce a method for extracting grapheme-to-phoneme conversion rules from the transcription of speech synthesis database and a prosody modeling method using the light version of ToBI for a Korean conversational style TTS. We focused on representing the characteristics of the conversational speech style and the experimental results show that our proposed methods are suitable for developing a Korean conversional style TTS.

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Decision-Tree-Based Markov Model for Phrase Break Prediction

  • Kim, Sang-Hun;Oh, Seung-Shin
    • ETRI Journal
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    • 제29권4호
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    • pp.527-529
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    • 2007
  • In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

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Prosodic Annotation in a Thai Text-to-speech System

  • Potisuk, Siripong
    • 한국언어정보학회:학술대회논문집
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    • 한국언어정보학회 2007년도 정기학술대회
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    • pp.405-414
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    • 2007
  • This paper describes a preliminary work on prosody modeling aspect of a text-to-speech system for Thai. Specifically, the model is designed to predict symbolic markers from text (i.e., prosodic phrase boundaries, accent, and intonation boundaries), and then using these markers to generate pitch, intensity, and durational patterns for the synthesis module of the system. In this paper, a novel method for annotating the prosodic structure of Thai sentences based on dependency representation of syntax is presented. The goal of the annotation process is to predict from text the rhythm of the input sentence when spoken according to its intended meaning. The encoding of the prosodic structure is established by minimizing speech disrhythmy while maintaining the congruency with syntax. That is, each word in the sentence is assigned a prosodic feature called strength dynamic which is based on the dependency representation of syntax. The strength dynamics assigned are then used to obtain rhythmic groupings in terms of a phonological unit called foot. Finally, the foot structure is used to predict the durational pattern of the input sentence. The aforementioned process has been tested on a set of ambiguous sentences, which represents various structural ambiguities involving five types of compounds in Thai.

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가변 운율 모델링을 이용한 고음질 감정 음성합성기 구현에 관한 연구 (A Study on Implementation of Emotional Speech Synthesis System using Variable Prosody Model)

  • 민소연;나덕수
    • 한국산학기술학회논문지
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    • 제14권8호
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    • pp.3992-3998
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    • 2013
  • 본 논문은 고음질의 대용량 코퍼스 기반 음성 합성기에 감정 음성 코퍼스를 추가하여 보다 다양한 합성음을 생성할 수 있는 방법에 관한 것이다. 파형 접합형 합성기에서 사용할 수 있는 형태로 감정 음성 코퍼스를 구축하여 기존의 일반 음성 코퍼스와 동일한 합성단위 선택과정을 통해 합성음을 생성할 수 있도록 구현하였다. 감정 음성 합성을 위해 태그를 사용하여 텍스트를 입력하고, 억양구 단위로 일치하는 데이터가 존재하는 경우 감정 음성으로 합성하고, 그렇지 않은 경우 일반 음성으로 합성하도록 하였다. 그리고 음성에서 운율을 구성하는 요소로 휴지기(break)가 있는데, 감정 음성의 휴지기는 일반 음성보다 불규칙한 특성이 있다. 따라서 합성기에서 생성되는 휴지기 정보를 감정 음성 합성에 그대로 사용하는 것이 어려워진다. 이 문제를 해결하기 위해 가변 휴지기(Variable break)[3] 모델링을 적용하였다. 실험은 일본어 합성기를 사용하였고, 그 결과 일반 음성의 휴지기 예측 모듈을 그대로 사용하면서 자연스러운 감정 합성음을 얻을 수 있었다.