Technical Program

SP-P3: Robust Speech Recognition II

Session Type: Poster

Time: Tuesday, March 16, 16:00 - 18:00

Location: Poster Area A

Session Chair: Jasha Droppo, Microsoft Research, USA

SP-P3.1: NOISE ROBUST EXEMPLAR-BASED CONNECTED DIGIT RECOGNITION

Jort Gemmeke; Radboud University Nijmegen

Tuomas Virtanen; Tampere University of Technology

SP-P3.2: ACOUSTIC MODEL ADAPTATION VIA LINEAR SPLINE INTERPOLATION FOR ROBUST SPEECH RECOGNITION

Michael Seltzer; Microsoft Research

Kaustubh Kalgaonkar; Georgia Institute of Technology

Alex Acero; Microsoft Research

SP-P3.3: HMM ADAPTATION USING SPARSE PROBABILISTIC SPACE MAPPING FOR NOISY SPEECH

Kaustubh Kalgaonkar; Georgia Institute of Technology

Mark Clements; Georgia Institute of Technology

SP-P3.4: EFFICIENT VQ-BASED MMSE ESTIMATION FOR ROBUST SPEECH RECOGNITION

José A. González; University of Granada

Antonio M. Peinado; University of Granada

Angel M. Gomez; University of Granada

José L. Carmona; University of Granada

Juan A. Morales-Cordovilla; University of Granada

SP-P3.5: NON-NEGATIVE MATRIX FACTORIZATION AS NOISE-ROBUST FEATURE EXTRACTOR FOR SPEECH RECOGNITION

Bjoern Schuller; Technische Universitaet Muenchen

Felix Weninger; Technische Universitaet Muenchen

Martin Woellmer; Technische Universitaet Muenchen

Yang Sun; Technische Universitaet Muenchen

Gerhard Rigoll; Technische Universitaet Muenchen

SP-P3.6: OPTIMIZING SPECTRAL SUBTRACTION AND WIENER FILTERING FOR ROBUST SPEECH RECOGNITION IN REVERBERANT AND NOISY CONDITIONS

Randy Gomez; Kyoto University

Tatsuya Kawahara; Kyoto University

SP-P3.7: HMM-BASED PSEUDO-CLEAN SPEECH SYNTHESIS FOR SPLICE ALGORITHM

Jun Du; University of Science and Technology of China

Yu Hu; University of Science and Technology of China

Li-Rong Dai; University of Science and Technology of China

Ren-Hua Wang; University of Science and Technology of China

SP-P3.8: FEATURE EXTRACTION FOR ROBUST SPEECH RECOGNITION BASED ON MAXIMIZING THE SHARPNESS OF THE POWER DISTRIBUTION AND ON POWER FLOORING

Chanwoo Kim; Carnegie Mellon University

Richard Stern; Carnegie Mellon University

SP-P3.9: HISTOGRAM EQUALIZATION AND NOISE MASKING FOR ROBUST SPEECH RECOGNITION

Xueru Zhang; Katholieke Universiteit Leuven

Kris Demuynck; Katholieke Universiteit Leuven

Hugo Van hamme; Katholieke Universiteit Leuven

SP-P3.10: A KERNEL MEAN MATCHING APPROACH FOR ENVIRONMENT MISMATCH COMPENSATION IN SPEECH RECOGNITION

Abhishek Kumar; University of Utah

John Hansen; University of Texas at Dallas

SP-P3.11: MAGNITUDE SPECTRUM ENHANCEMENT FOR ROBUST SPEECH RECOGNITION

Wen-Hsiang Tu; National Chi Nan University

Jeih-weih Hung; National Chi Nan University

SP-P3.12: AUDITORY MODEL BASED MODIFIED MFCC FEATURES

Saikat Chatterjee; KTH - Royal Institute of Technology

W. Bastiaan Kleijn; KTH - Royal Institute of Technology