25.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Central European Institute of TechnologyCZ145 papers
- Centre National de la Recherche ScientifiqueFR42 papers
- Masaryk UniversityCZ41 papers
- TU WienAT34 papers
- Université Grenoble AlpesFR24 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ22 papers
- University of ViennaAT21 papers
- Charles UniversityCZ17 papers
- Central European Institute of Technology – Masaryk UniversityCZ16 papers
- Kempelen Institute of Intelligent Technologies13 papers
- Laboratoire National des Champs Magnétiques IntensesFR13 papers
- Military University of Technology in WarsawPL13 papers
7 papers · 2 filters
On the use of DNN Autoencoder for Robust Speaker Recognition
Ondrej Novotny, Oldrich Plchot, Pavel Matejka +1
In this paper, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker recognition syste…
Promising Accurate Prefix Boosting for sequence-to-sequence ASR
Murali Karthick Baskar, Lukáš Burget, Shinji Watanabe +3
In this paper, we present promising accurate prefix boosting (PAPB), a discriminative training technique for attention based sequence-to-sequence (seq2seq) ASR. PAPB is devised to…
Building and Evaluation of a Real Room Impulse Response Dataset
Igor Szoke, Miroslav Skacel, Ladislav Mosner +2
This paper presents BUT ReverbDB - a dataset of real room impulse responses (RIR), background noises and re-transmitted speech data. The retransmitted data includes LibriSpeech tes…
Language model integration based on memory control for sequence to sequence speech recognition
Jaejin Cho, Shinji Watanabe, Takaaki Hori +4
In this paper, we explore several new schemes to train a seq2seq model to integrate a pre-trained LM. Our proposed fusion methods focus on the memory cell state and the hidden stat…
A Proper version of Synthesis-based Sparse Audio Declipper
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý +1
Methods based on sparse representation have found great use in the recovery of audio signals degraded by clipping. The state of the art in declipping has been achieved by the SPADE…
Convolutional Neural Networks and x-vector Embedding for DCASE2018 Acoustic Scene Classification Challenge
Hossein Zeinali, Lukas Burget, Jan Cernocky
In this paper, the Brno University of Technology (BUT) team submissions for Task 1 (Acoustic Scene Classification, ASC) of the DCASE-2018 challenge are described. Also, the analysi…
Revisiting Synthesis Model of Sparse Audio Declipper
Pavel Záviška, Pavel Rajmic, Zdeněk Průša +1
The state of the art in audio declipping has currently been achieved by SPADE (SParse Audio DEclipper) algorithm by Kitić et al. Until now, the synthesis/sparse variant, S-SPADE, h…