• Title/Summary/Keyword: prosody modeling

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

  • Kim, Seung-Won;Zheng, Yu;Lee, Gary-Geunbae;Kim, Byeong-Chang
    • MALSORI
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    • no.53
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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
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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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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Implementation of Korean TTS System based on Natural Language Processing (자연어 처리 기반 한국어 TTS 시스템 구현)

  • Kim Byeongchang;Lee Gary Geunbae
    • MALSORI
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    • no.46
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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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A Study of Decision Tree Modeling for Predicting the Prosody of Corpus-based Korean Text-To-Speech Synthesis (한국어 음성합성기의 운율 예측을 위한 의사결정트리 모델에 관한 연구)

  • Kang, Sun-Mee;Kwon, Oh-Il
    • Speech Sciences
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    • v.14 no.2
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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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Grapheme-to-Phoneme Conversion and Prosody Modeling for Korean Conversational Style TTS (한국어 대화체 TTS 개발을 위한 발음 및 운율 추정)

  • Lee, Jin-Sik;Kim, Seung-Won;Kim, Byeong-Chang;Lee, Geun-Bae
    • Proceedings of the KSPS conference
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    • 2006.11a
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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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    • v.29 no.4
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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
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2007.11a
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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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A Study on Implementation of Emotional Speech Synthesis System using Variable Prosody Model (가변 운율 모델링을 이용한 고음질 감정 음성합성기 구현에 관한 연구)

  • Min, So-Yeon;Na, Deok-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.8
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    • pp.3992-3998
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    • 2013
  • This paper is related to the method of adding a emotional speech corpus to a high-quality large corpus based speech synthesizer, and generating various synthesized speech. We made the emotional speech corpus as a form which can be used in waveform concatenated speech synthesizer, and have implemented the speech synthesizer that can be generated various synthesized speech through the same synthetic unit selection process of normal speech synthesizer. We used a markup language for emotional input text. Emotional speech is generated when the input text is matched as much as the length of intonation phrase in emotional speech corpus, but in the other case normal speech is generated. The BIs(Break Index) of emotional speech is more irregular than normal speech. Therefore, it becomes difficult to use the BIs generated in a synthesizer as it is. In order to solve this problem we applied the Variable Break[3] modeling. We used the Japanese speech synthesizer for experiment. As a result we obtained the natural emotional synthesized speech using the break prediction module for normal speech synthesize.