Develoment of Spoken Dialogue System for Japanese and Chinese

日汉口语对话系统的开发

• 批准号: 08558028
• 负责人: HIROSE Keikichi
• 金额: $ 5.12万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (A)
• 财政年份: 1996
• 资助国家: 日本
• 起止时间: 1996 至 1998
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08558028/
• 关键词: Spoken Dialogue System; Speech Recognition; Speech Synthesis; Multi-lingual System; Viterbi Bayesian Predictive Classification; Waveform Concatenation Synthesis; Prosodic Modelig; Tone Recognition; ビタビ探索; TD-PSOLA; 対話処理; 言語自動識別; ベイズ予測分類; HMM

With the aim of developing a spoken dialogue system for both Japanese and Chinese in order to check the possibility of realizing practical systems of multilingual spoken dialogue, the following major results were obtained.1. After selecting literature retrieval as the system task, we have arranged necessary databases and installed dictionary for speech synthesis. Also a speech corpus was cotstructed for training and evaluating speech recognition.2. Phoneme HMM's and phoneme class HMM's were trained using the corpus. A method was developed to identify the input speech being Japanese or Chinese based on the phoneme/phoneme class sequences.3. A robust speech recognition method was developed based on Bayesian predictive classification with Viterbi approximation. An adaptation method was further proposed, where improved posterior probability density function was estimated via sequential Bayesian learning using adaptation data. Another robust method, minimax, was also investigated to make it … More applicable to continuous speech.4. An automatic Waveform concatenation speech synthesis method was developed. This method is based on segmenting speech waveform using speech recognition technique, and automatically placing pitch marks after LMA analysis. It was utilized for the Chinese speech synthesis.5. Waveform concatenation synthesizer was combined with formant synthesizer to generate a new speech synthesis system. This system was shown to improve several low quality phonemes.6. A speech synthesis oriented modeling of ; Chinese prosody was developed based on the newly defined function for unified representation of Chinese fundamental frequency contours.7. A method was developed for precise tone recognition of Chinese continuous speech. This method is based on using features of tone nucleus of a syllable only.8. A Japanese/Chinese spoken dialogue system was constructed (or literature retrieval. Chinese responses were pre-stored sentences, while Japanese responses were generated from semantic representations. The system was confirmed to operate both in Japanese and Chinese. Less

本研究以开发日语和汉语的口语对话系统为目的，为了验证实现多语言口语对话的实用系统的可能性，取得了以下主要成果。1.在选择了文献检索作为系统任务后，我们安排了必要的数据库，安装了语音合成词典。并建立了语音语料库，用于语音识别的训练和评价.使用语料库训练音素HMM和音素类HMM。提出了一种基于音素/音素类序列识别输入语音是日语还是汉语的方法.提出了一种基于Viterbi近似的贝叶斯预测分类的鲁棒语音识别方法。进一步提出了一种自适应方法，利用自适应数据通过序贯贝叶斯学习估计改进的后验概率密度函数。另一个强大的方法，极大极小，也进行了研究，使之 ...更多信息 适用于连续语音。提出了一种波形拼接语音自动合成方法。该方法基于语音识别技术对语音波形进行分段，并在LMA分析后自动放置基音标记。并将其用于汉语语音合成.将波形级联合成器与共振峰合成器相结合，构成一种新的语音合成系统。该系统被证明可以改善几个低质量的手机。基于新定义的基频轮廓统一表示函数，实现了面向语音合成的汉语韵律建模.提出了一种汉语连续语音声调的精确识别方法。该方法仅利用了音节的声核特征.构建了一个日汉口语对话系统（或文献检索系统）。中文的反应是预先存储的句子，而日语的反应是从语义表征产生的。该系统已被确认为日语和中文操作。少

项目成果

Hui Jiang, Keikichi Hirose and Qiang Huo: "Sequential Bayesian learning of CDHMM based on finite mixture approximation of its prior/posterior density" Proc.IEEE Automatic Speech Recognition Workshop, IEEE SP Society. 373-380 (1997)

Hui Jiang、Keikichi Hirose 和 Gang Huo：“基于先验/后验密度的有限混合近似的 CDHMM 的顺序贝叶斯学习”Proc.IEEE 自动语音识别研讨会，IEEE SP 协会。

広瀬啓吉: "Use of prosodic features in speech recognition (Invited)" Proc. IEEE Invited Workshop on Pattern Recognition for Multimedia Techniques (IEEE Taegu Section). 99-108 (1996)

Keikichi Hirose：“语音识别中韵律特征的使用（特邀）”Proc. IEEE 多媒体技术模式识别研讨会（IEEE 大邱部分）。

Keikichi Hirose, Mayumi Sakata and Hiromichi Kawanami: "Synthesizing dialogue speech of Japanese based on the quantitative analysis of prosodic features" Proc. International Conference on Spoken Language Processing, 1. 378-381 (1996)

Keikichi Hirose、Mayumi Sakata 和 Hiromichi Kawanami：“基于韵律特征定量分析的日语对话语音合成”Proc.

MERON Yoram: "Waveform concatenation speech synthesis using phonetic clustering and automatic unit selection" 日本音響学会平成9年度秋季研究発表会講演論文集. I. 263-264 (1997)

MERON Yoram：“使用语音聚类和自动单元选择的波形串联语音合成”日本声学学会 1997 年秋季研究会议论文集 I. 263-264 (1997)。

広瀬啓吉: "対話音声の生成(「音声による人間と機械の対話」の第4章)"オーム社. 375 14 (1998)

Keikichi Hirose：“对话语音的生成（《使用语音的人机对话》第 4 章）” Ohmsha 375 14 (1998)。