Technical Program
SP-P3: Features for Robust Automatic Speech Recognition |
| Session Type: Poster |
| Time: Tuesday, May 28, 15:30 - 17:30 |
| Location: Poster Area C |
| Session Chair: Qi Li, Creative Technologies Inc. |
| SP-P3.1: COMBINING WINDOW PREDICTIONS EFFICIENTLY - A NEW IMPUTATION APPROACH FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION |
| Qun Feng Tan; University of Southern California |
| Shrikanth Narayanan; University of Southern California |
| SP-P3.2: NOISE MODEL TRANSFER USING AFFINE TRANSFORMATION WITH APPLICATION TO LARGE VOCABULARY REVERBERANT SPEECH RECOGNITION |
| Takuya Yoshioka; Nippon Telegraph and Telephone Corporation |
| Tomohiro Nakatani; Nippon Telegraph and Telephone Corporation |
| SP-P3.3: SPECTRO-TEMPORAL FEATURES FOR NOISE-ROBUST SPEECH RECOGNITION USING POWER-LAW NONLINEARITY AND POWER-BIAS SUBTRACTION |
| Shuo-Yiin Chang; University of California, Berkeley |
| Bernd T. Meyer; University of Oldenburg |
| Nelson Morgan; International Computer Science Institute |
| SP-P3.4: RECOGNITION OF OVERLAPPING SPEECH USING DIGITAL MEMS MICROPHONE ARRAYS |
| Erich Zwyssig; EADS |
| Friedrich Faubel; Saarland University |
| Steve Renals; The University of Edinburgh |
| Mike Lincoln; Quorate Technology Ltd. |
| SP-P3.5: STEREO-BASED FEATURE ENHANCEMENT USING DICTIONARY LEARNING |
| Shinji Watanabe; Mitsubishi Electric Research Laboratories (MERL) |
| John R. Hershey; Mitsubishi Electric Research Laboratories (MERL) |
| SP-P3.6: A VTS-BASED FEATURE COMPENSATION APPROACH TO NOISY SPEECH RECOGNITION USING MIXTURE MODELS OF DISTORTION |
| Jun Du; University of Science and Technology of China |
| Qiang Huo; Microsoft Research Asia |
| SP-P3.7: AN ADVANCED FEATURE COMPENSATION METHOD EMPLOYING ACOUSTIC MODEL WITH PHONETICALLY CONSTRAINED STRUCTURE |
| Wooil Kim; Incheon National University |
| John H.L. Hansen; The University of Texas at Dallas |
| SP-P3.8: NOISE AWARE MANIFOLD LEARNING FOR ROBUST SPEECH RECOGNITION |
| Vikrant Tomar; McGill University |
| Richard Rose; McGill University |
| SP-P3.9: IDEAL RATIO MASK ESTIMATION USING DEEP NEURAL NETWORKS FOR ROBUST SPEECH RECOGNITION |
| Arun Narayanan; The Ohio State University |
| DeLiang Wang; The Ohio State University |
| SP-P3.10: A ROBUST FRONTEND FOR ASR: COMBINING DENOISING, NOISE MASKING AND FEATURE NORMALIZATION |
| Maarten Van Segbroeck; University of Southern California |
| Shrikanth Narayanan; University of Southern California |
| SP-P3.11: FILTER-BANK OPTIMIZATION FOR FREQUENCY DOMAIN LINEAR PREDICTION |
| Vijayaditya Peddinti; Johns Hopkins University |
| Hynek Hermansky; Johns Hopkins University |
| SP-P3.12: AN MCMC APPROACH TO JOINT ESTIMATION OF CLEAN SPEECH AND NOISE FOR ROBUST SPEECH RECOGNITION |
| Aleem Mushtaq; Georgia Institute of Technology |
| Chin-Hui Lee; Georgia Institute of Technology |
| SP-P3.13: FILTERING ON THE TEMPORAL PROBABILITY SEQUENCE IN HISTOGRAM EQUALIZATION FOR ROBUST SPEECH RECOGNITION |
| Syu-Siang Wang; Academia Sinica |
| Yu Tsao; Academia Sinica |
| Jeih-weih Hung; National Chi Nan University |
| SP-P3.14: JOINT SPARSE REPRESENTATION BASED CEPSTRAL-DOMAIN DEREVERBERATION FOR DISTANT-TALKING SPEECH RECOGNITION |
| Weifeng Li; Tsinghua University |
| Longbiao Wang; Nagaoka University |
| Fei Zhou; Tsinghua University |
| Qingmin Liao; Tsinghua University |