Construction of Audio-Visual Speech Corpus Using Motion-Capture System and Corpus Based Facial Animation(<Special Section>Life-like Agent and its Communication)
スポンサーリンク
概要
- 論文の詳細を見る
An accurate audio-visual speech corpus is inevitable for talking-heads research. This paper presents our audio-visual speech corpus collection and proposes a head-movement normalization method and a facial motion generation method. The audio-visual corpus contains speech data, movie data on faces, and positions and movements of facial organs. The corpus consists of Japanese phoneme-balanced sentences uttered by a female native speaker. An accurate facial capture is realized by using an optical motion-capture system. We captured high-resolution 3D data by arranging many markers on the speaker's face. In addition, we propose a method of acquiring the facial movements and removing head movements by using affine transformation for computing displacements of pure facial organs. Finally, in order to easily create facial animation from this motion data, we propose a technique assigning the captured data to the facial polygon model. Evaluation results demonstrate the effectiveness of the proposed facial motion generation method and show the relationship between the number of markers and errors.
- 社団法人電子情報通信学会の論文
- 2005-11-01
著者
-
NAKAMURA Satoshi
ATR Spoken Language Translation Research Labs.
-
Morishima Shigeo
Atr Spoken Language Communication Research Laboratories:waseda University
-
YOTSUKURA Tatsuo
ATR Spoken Language Communication Research Laboratories
-
Nakamura Satoshi
Atr Spoken Language Translation Res. Lab. Kyoto Jpn
-
Nakamura Satoshi
Atr Spoken Language Communication Res. Lab. Kyoto‐fu Jpn
-
Nakamura Satoshi
Atr Spoken Language Communication Research Laboratories
関連論文
- Combination Therapy with Vascular Endothelial Growth Factor Neutralizing Antibody and Mitomycin C on Human Gastric Cancer Xenograft
- Noise and Channel Distortion Robust ASR System for DARPA SPINE2 Task (Special Issue on Speech Information Processing)
- A Study on Acoustic Modeling of Pauses for Recognizing Noisy Conversational Speech (Special Issue on Speech Information Processing)
- AURORA-2J: An Evaluation Framework for Japanese Noisy Speech Recognition(Speech Corpora and Related Topics, Corpus-Based Speech Technologies)
- Missing Feature Theory Applied to Robust Speech Recognition over IP Network(Speech Dynamics by Ear, Eye, Mouth and Machine)
- CENSREC-3: An Evaluation Framework for Japanese Speech Recognition in Real Car-Driving Environments(Speech and Hearing)
- A Design for a Collaborative Steering System of Microphone Array and Video Camera Toward Multi-Lingual Tele-Conference (特集 インタラクション技術の革新と実用化)
- A design of adaptive beamformer based on average speech spectrum for noisy speech recognition
- A Microphone Array-Based 3-D N-Best Search Method for Recognizing Multiple Sound Sources
- The present status, progress, and usage of speech databases in Japan
- IMPROVING ACCURACY IN PARAMETER ESTIMATION IN AN EXTENDED KALMAN PARTICLE FILTERS FOR NOISY SPEECH RECOGNITION
- ATR Parallel Decoding Based Speech Recognition System Robust to Noise and Speaking Styles(Speech Recognition, Statistical Modeling for Speech Processing)
- Construction of Audio-Visual Speech Corpus Using Motion-Capture System and Corpus Based Facial Animation(Life-like Agent and its Communication)
- Passive hybrid subtractive beamformer for near-field sound sources
- An Acoustic Modeling Method Robustagainst Changes of Speaking Stylein Error Recovery
- A Hybrid HMM/BN Acoustic Model Utilizing Pentaphone-Context Dependency(Speech Recognition, Statistical Modeling for Speech Processing)
- Improving Acoustic Model Precision by Incorporating a Wide Phonetic Context Based on a Bayesian Framework(Speech Recognition, Statistical Modeling for Speech Processing)
- A Hybrid HMM/BN Acoustic Model for Automatic Speech Recognition (Special Issue on Speech Information Processing)
- MIXTURE OF FACTOR ANALYZED HMM
- Iterative Estimation and Compensation of Signal Direction for Moving Sound Source by Mobile Microphone Array(Engineering Acoustics)
- TIME-VARYING NOISE COMPENSATION BY SEQUENTIAL MONTE CARLO METHOD
- Burst Error Recovery for Huffman Coding(Algorithm Theory)
- Audio-Visual Speech Recognition Based on Optimized Product HMMs and GMM Based-MCE-GPD Stream Weight Estimation (Special Issue on Speech Information Processing)