activity
20202023
most citedNeural Target Speech Extraction: An Overview

120 citations · 139 across the 6 of their papers we have counts for

collaborators

8 papers

eess.AS2023★ 120 cited

Neural Target Speech Extraction: An Overview

Katerina Zmolikova, Marc Delcroix, Tsubasa Ochiai +3

Humans can listen to a target speaker even in challenging acoustic conditions that have noise, reverberation, and interfering speakers. This phenomenon is known as the cocktail-par…

eess.AS2022★ 3 cited

Listen only to me! How well can target speech extraction handle false alarms?

Marc Delcroix, Keisuke Kinoshita, Tsubasa Ochiai +3

Target speech extraction (TSE) extracts the speech of a target speaker in a mixture given auxiliary clues characterizing the speaker, such as an enrollment utterance. TSE addresses…

eess.AS2021

Revisiting joint decoding based multi-talker speech recognition with DNN acoustic model

Martin Kocour, Kateřina Žmolíková, Lucas Ondel +5

In typical multi-talker speech recognition systems, a neural network-based acoustic model predicts senone state posteriors for each speaker. These are later used by a single-talker…

eess.AS2021★ 4 cited

Speaker activity driven neural speech extraction

Marc Delcroix, Katerina Zmolikova, Tsubasa Ochiai +2

Target speech extraction, which extracts the speech of a target speaker in a mixture given auxiliary speaker clues, has recently received increased interest. Various clues have bee…

eess.AS2020

Integration of variational autoencoder and spatial clustering for adaptive multi-channel neural speech separation

Katerina Zmolikova, Marc Delcroix, Lukáš Burget +2

In this paper, we propose a method combining variational autoencoder model of speech with a spatial clustering approach for multi-channel speech separation. The advantage of integr…

cs.SD2020

Jointly Trained Transformers models for Spoken Language Translation

Hari Krishna Vydana, Martin Karafi'at, Katerina Zmolikova +2

Conventional spoken language translation (SLT) systems are pipeline based systems, where we have an Automatic Speech Recognition (ASR) system to convert the modality of source from…

eess.AS2020

BUT System for the Second DIHARD Speech Diarization Challenge

Federico Landini, Shuai Wang, Mireia Diez +9

This paper describes the winning systems developed by the BUT team for the four tracks of the Second DIHARD Speech Diarization Challenge. For tracks 1 and 2 the systems were mainly…

eess.AS2020★ 12 cited

Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam

Marc Delcroix, Tsubasa Ochiai, Katerina Zmolikova +4

Target speech extraction, which extracts a single target source in a mixture given clues about the target speaker, has attracted increasing attention. We have recently proposed Spe…