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speech recognition
Description
Publications
- Binary Non-Negative Matrix Deconvolution for Audio Dictionary Learning
- Exemplar-based speech enhancement for deep neural network based automatic speech recognition
- Coupled dictionaries for exemplar-based speech enhancement and automatic speech recognition
- Robust Speech Recognition with Spectrogram Factorisation
- The TUM+TUT+KUL Approach to the 2nd CHiME Challenge: Multi-Stream ASR Exploiting BLSTM Networks and Sparse NMF
- HMM-regularization for NMF-based noise robust ASR
- The TUM+TUT+KUL Approach to the CHiME Challenge 2013: Multi-Stream ASR Exploiting BLSTM Networks and Sparse NMF
- HMM-Regularization for NMF-Based Noise Robust ASR
- Compact Long Context Spectral Factorisation Models for Noise Robust Recognition of Medium Vocabulary Speech
- Acquiring Variable Length Speech Bases for Factorisation-Based Noise Robust Speech Recognition
- Learning State Labels for Sparse Classification of Speech with Matrix Deconvolution
- Modelling Non-stationary Noise with Spectral Factorisation in Automatic Speech Recognition
- Avainsanojen tunnistusratkaisujen testaus
- Non-Negative Matrix Factorization for Highly Noise-Robust ASR: to Enhance or to Recognize?
- Modelling spectro-temporal dynamics in factorisation-based noise-robust automatic speech recognition
- Detection, Separation and Recognition of Speech From Continuous Signals Using Spectral Factorisation
- Toward A Practical Implementation Of Exemplar-Based Noise Robust ASR
- Mapping Sparse Representation to State Likelihoods in Noise-Robust Automatic Speech Recognition
- Esimerkkipohjainen meluisan puheen automaattinen tunnistus
- Non-negative matrix deconvolution in noise robust speech recognition
- Exemplar-based Recognition of Speech in Highly Variable Noise
- Exemplar-based Sparse Representations for Noise Robust Automatic Speech Recognition
- Toward a Practical Implementation of Exemplar-Based Noise Robust ASR
- Exemplar-Based Speech Enhancement and its Application to Noise-Robust Automatic Speech Recognition
- Artificial and online acquired noise dictionaries for noise robust ASR
- State-based labelling for a sparse representation of speech and its application to robust speech recognition