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NIPS
2001
13 years 8 months ago
Speech Recognition with Missing Data using Recurrent Neural Nets
In the `missing data' approach to improving the robustness of automatic speech recognition to added noise, an initial process identifies spectraltemporal regions which are do...
S. Parveen, P. Green
ICASSP
2011
IEEE
12 years 11 months ago
Learning vocal tract variables with multi-task kernels
The problem of acoustic-to-articulatory speech inversion continues to be a challenging research problem which significantly impacts automatic speech recognition robustness and ac...
Hachem Kadri, Emmanuel Duflos, Philippe Preux
ICMCS
2005
IEEE
134views Multimedia» more  ICMCS 2005»
14 years 27 days ago
Relevance Feedback Methods in Content Based Retrieval and Video Summarization
In the current state-of-the-art in multimedia content analysis (MCA), the fundamental techniques are typically derived from core pattern recognition and computer vision algorithms...
Micha Haas, Ard Oerlemans, Michael S. Lew
ICASSP
2011
IEEE
12 years 11 months ago
Delta-spectral cepstral coefficients for robust speech recognition
Almost all current automatic speech recognition (ASR) systems conventionally append delta and double-delta cepstral features to static cepstral features. In this work we describe ...
Kshitiz Kumar, Chanwoo Kim, Richard M. Stern
ICASSP
2011
IEEE
12 years 11 months ago
Robust speech recognition using dynamic noise adaptation
Dynamic noise adaptation (DNA) [1, 2] is a model-based technique for improving automatic speech recognition (ASR) performance in noise. DNA has shown promise on artificially mixe...
Steven J. Rennie, Pierre L. Dognin, Petr Fousek