| Author | Session | Pages | Title |
A  A B C D E F G H I J K L M N O P R S T U W Y Z |
| Adiloglu, Kamil | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Adiloglu, Kamil | Poster | 31-32 | Using full-rank spatial covariance models for noise-robust ASR |
| Astudillo, Ramon Fernandez | Poster | 33-38 | A flexible spatial blind source extraction framework for robust speech recognition in noisy environments |
| B A B C D E F G H I J K L M N O P R S T U W Y Z |
| Bardeli, Rolf | Poster | 71-72 | Employing stochastic constrained LMS algorithm for ASR frontend processing |
| Barker, Jon | Poster | 53-58 | A fragment-decoding plus missing-data imputation ASR system evaluated on the 2nd CHiME Challenge |
| C A B C D E F G H I J K L M N O P R S T U W Y Z |
| Chambers, Jonathon | Poster | 83-84 | Speech separation with dereverberation-based pre-processing incorporating visual cues |
| D A B C D E F G H I J K L M N O P R S T U W Y Z |
| Duan, Zhiyao | Poster | 85-86 | Approaches to multiple concurrent species bird song recognition |
| Doclo, Simon | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| E A B C D E F G H I J K L M N O P R S T U W Y Z |
| Espy-Wilson, Carol Y. | Poster | 65 | Fusion of acoustic, perceptual and production features for noise robust speech recognition in highly non-stationary noise |
| F A B C D E F G H I J K L M N O P R S T U W Y Z |
| G A B C D E F G H I J K L M N O P R S T U W Y Z |
| Geiger, Jürgen T. | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Geiger, Jürgen | Oral 2 | 86-90 | The Munich feature enhancement approach to the 2nd CHiME Challenge using BLSTM recurrent neural networks |
| Gemmeke, Jort F. | Oral 1 | 13-18 | Compact long context spectral factorization models for noise robust recognition of medium vocabulary speech |
| Gemmek, Jort F. | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Gemmeke, Jort F. | Poster | 39-43 | Noise-robust automatic speech recognition with exemplar-based sparse representations using multiple length adaptive dictionaries |
| Gemmeke, Jort F. | Poster | 47-52 | HMM-regularization for NMF-based noise robust ASR |
| Gerkmann, Timo | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Goetze, Stefan | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| H A B C D E F G H I J K L M N O P R S T U W Y Z |
| Hagmüller, Martin | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| Hannun, Awni Y. | Poster | 79-80 | Recurrent neural network feature enhancement: The 2nd CHiME Challenge |
| Hershey, John R. | Oral 1 | 19-24 | Discriminative methods for noise robust speech recognition: A CHiME Challenge benchmark |
| Hurmalainen, Antti | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Hurmalainen, Antti | Poster | 47-52 | HMM-regularization for NMF-based noise robust ASR |
| Hurmalainen, Antti | Oral 1 | 13-18 | Compact long context spectral factorization models for noise robust recognition of medium vocabulary speech |
| I A B C D E F G H I J K L M N O P R S T U W Y Z |
| J A B C D E F G H I J K L M N O P R S T U W Y Z |
| Jouvet, Denis | Poster | 31-32 | Using full-rank spatial covariance models for noise-robust ASR |
| Jürgens, Tim | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| K A B C D E F G H I J K L M N O P R S T U W Y Z |
| Kallasjoki, Heikki | Poster | 77-78 | Noise robust missing data mask estimation based on automatically learned features |
| Keronen, Sami | Poster | 77-78 | Noise robust missing data mask estimation based on automatically learned features |
| Khan, Muhammad Salman | Poster | 83-84 | Speech separation with dereverberation-based pre-processing incorporating visual cues |
| Kollmeier, Birger | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Kolossa, Dorothea | Oral 1 | 7-12 | Binaural signal processing for enhanced speech recognition robustness in complex listening environments |
| Kubin, Gernot | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| L A B C D E F G H I J K L M N O P R S T U W Y Z |
| Le Roux, Jonathan | Oral 1 | 19-24 | Discriminative methods for noise robust speech recognition: A CHiME Challenge benchmark |
| M A B C D E F G H I J K L M N O P R S T U W Y Z |
| Ma, Ning | Poster | 53-58 | A fragment-decoding plus missing-data imputation ASR system evaluated on the 2nd CHiME Challenge |
| Maas, Andrew L. | Poster | 79-80 | Recurrent neural network feature enhancement: The 2nd CHiME Challenge |
| Matassoni, Marco | Poster | 33-38 | A flexible spatial blind source extraction framework for robust speech recognition in noisy environments |
| Meutzner, Hendrik | Oral 1 | 7-12 | Binaural signal processing for enhanced speech recognition robustness in complex listening environments |
| Meyer, Bernd T. | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Mitra, Vikramjit | Poster | 65 | Fusion of acoustic, perceptual and production features for noise robust speech recognition in highly non-stationary noise |
| Morales-Cordovilla, Juan A. | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| Moritz, Niko | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Mowlaee, Pejman | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| N A B C D E F G H I J K L M N O P R S T U W Y Z |
| Naqvi, Syed Mohsen | Poster | 83-84 | Speech separation with dereverberation-based pre-processing incorporating visual cues |
| Nesta, Francesco | Poster | 33-38 | A flexible spatial blind source extraction framework for robust speech recognition in noisy environments |
| Ng, Andrew Y. | Poster | 79-80 | Recurrent neural network feature enhancement: The 2nd CHiME Challenge |
| O A B C D E F G H I J K L M N O P R S T U W Y Z |
| O’Neil, Tyler M. | Poster | 79-80 | Recurrent neural network feature enhancement: The 2nd CHiME Challenge |
| P A B C D E F G H I J K L M N O P R S T U W Y Z |
| Palomäki, Kalle | Poster | 77-78 | Noise robust missing data mask estimation based on automatically learned features |
| Pardo, Bryan | Poster | 85-86 | Approaches to multiple concurrent species bird song recognition |
| Pernkopf, Franz | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| Pessentheiner, Hannes | Poster | 59-64 | The 2nd `CHiME' Speech Separation and Recognition Challenge: Approaches on single-channel speech separation and model-driven speech enhancement |
| Q A B C D E F G H I J K L M N O P R S T U W Y Z |
| R A B C D E F G H I J K L M N O P R S T U W Y Z |
| Remes, Ulpu | Poster | 77-78 | Noise robust missing data mask estimation based on automatically learned features |
| Rigoll, Gerhard | Oral 2 | 86-90 | The Munich feature enhancement approach to the 2nd CHiME Challenge using BLSTM recurrent neural networks |
| Rigoll, Gerhard | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| S A B C D E F G H I J K L M N O P R S T U W Y Z |
| Schädler, Marc René | Oral 1 | 1-6 | Noise robust distant automatic speech recognition utilizing NMF based source separation and auditory feature extraction |
| Schlesinger, Anton | Oral 1 | 7-12 | Binaural signal processing for enhanced speech recognition robustness in complex listening environments |
| Schuller, Björn | Oral 2 | 86-90 | The Munich feature enhancement approach to the 2nd CHiME Challenge using BLSTM recurrent neural networks |
| Schuller, Björn | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Sivaraman, Ganesh | Poster | 65 | Fusion of acoustic, perceptual and production features for noise robust speech recognition in highly non-stationary noise |
| Springer, Jonathan | Poster | 85-86 | Approaches to multiple concurrent species bird song recognition |
| Stadtschnitzer, Michael | Poster | 71-72 | Employing stochastic constrained LMS algorithm for ASR frontend processing |
| Stein, Daniel | Poster | 71-72 | Employing stochastic constrained LMS algorithm for ASR frontend processing |
| T A B C D E F G H I J K L M N O P R S T U W Y Z |
| Tachioka, Yuuki | Oral 1 | 19-24 | Discriminative methods for noise robust speech recognition: A CHiME Challenge benchmark |
| Tran, Dung T. | Poster | 31-32 | Using full-rank spatial covariance models for noise-robust ASR |
| U A B C D E F G H I J K L M N O P R S T U W Y Z |
| V A B C D E F G H I J K L M N O P R S T U W Y Z |
| Van hamme, Hugo | Poster | 39-43 | Noise-robust automatic speech recognition with exemplar-based sparse representations using multiple length adaptive dictionaries |
| Vincent, Emmanuel | Poster | 31-32 | Using full-rank spatial covariance models for noise-robust ASR |
| Virtanen, Tuomas | Oral 1 | 13-18 | Compact long context spectral factorization models for noise robust recognition of medium vocabulary speech |
| Virtanen, Tuomas | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Virtanen, Tuomas | Poster | 47-52 | HMM-regularization for NMF-based noise robust ASR |
| W A B C D E F G H I J K L M N O P R S T U W Y Z |
| Watanabe, Shinji | Oral 1 | 19-24 | Discriminative methods for noise robust speech recognition: A CHiME Challenge benchmark |
| Weninger, Felix | Oral 2 | 86-90 | The Munich feature enhancement approach to the 2nd CHiME Challenge using BLSTM recurrent neural networks |
| Weninger, Felix | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| Wöllmer, Martin | Oral 2 | 86-90 | The Munich feature enhancement approach to the 2nd CHiME Challenge using BLSTM recurrent neural networks |
| Wöllmer, Martin | Poster | 25-30 | The TUM+TUT+KUL approach to the 2nd CHiME Challenge: Multi-stream ASR exploiting BLSTM networks and sparse NMF |
| X A B C D E F G H I J K L M N O P R S T U W Y Z |
| Y A B C D E F G H I J K L M N O P R S T U W Y Z |
| Yılmaz, Emre | Poster | 39-43 | Noise-robust automatic speech recognition with exemplar-based sparse representations using multiple length adaptive dictionaries |
| Z A B C D E F G H I J K L M N O P R S T U W Y Z |
| Zeiler, Steffen | Oral 1 | 7-12 | Binaural signal processing for enhanced speech recognition robustness in complex listening environments |