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20172024
most citedAcoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge

6 citations · 30 across the 24 of their papers we have counts for

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Showing 2018 · eess.ASShow all

5 papers · 2 filters

eess.AS2018

Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek +2

In this work, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker verification (SV)…

eess.AS2018

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…

eess.AS2018

Speaker verification using end-to-end adversarial language adaptation

Johan Rohdin, Themos Stafylakis, Anna Silnova +3

In this paper we investigate the use of adversarial domain adaptation for addressing the problem of language mismatch between speaker recognition corpora. In the context of speaker…

eess.AS2018

Discriminatively Re-trained i-vector Extractor for Speaker Recognition

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek +2

In this work we revisit discriminative training of the i-vector extractor component in the standard speaker verification (SV) system. The motivation of our research lies in the rob…

eess.AS2018

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…