19 citations · 21 across the 6 of their papers we have counts for
9 papers
Multi-Stream Extension of Variational Bayesian HMM Clustering (MS-VBx) for Combined End-to-End and Vector Clustering-based Diarization
Marc Delcroix, Naohiro Tawara, Mireia Diez +6
Combining end-to-end neural speaker diarization (EEND) with vector clustering (VC), known as EEND-VC, has gained interest for leveraging the strengths of both methods. EEND-VC esti…
Multi-Speaker and Wide-Band Simulated Conversations as Training Data for End-to-End Neural Diarization
Federico Landini, Mireia Diez, Alicia Lozano-Diez +1
End-to-end diarization presents an attractive alternative to standard cascaded diarization systems because a single system can handle all aspects of the task at once. Many flavors…
Speaker adaptation for Wav2vec2 based dysarthric ASR
Murali Karthick Baskar, Tim Herzig, Diana Nguyen +4
Dysarthric speech recognition has posed major challenges due to lack of training data and heavy mismatch in speaker characteristics. Recent ASR systems have benefited from readily…
From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization
Federico Landini, Alicia Lozano-Diez, Mireia Diez +1
End-to-end neural diarization (EEND) is nowadays one of the most prominent research topics in speaker diarization. EEND presents an attractive alternative to standard cascaded diar…
Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: theory, implementation and analysis on standard tasks
Federico Landini, Ján Profant, Mireia Diez +1
The recently proposed VBx diarization method uses a Bayesian hidden Markov model to find speaker clusters in a sequence of x-vectors. In this work we perform an extensive compariso…
Analysis of the BUT Diarization System for VoxConverse Challenge
Federico Landini, Ondřej Glembek, Pavel Matějka +4
This paper describes the system developed by the BUT team for the fourth track of the VoxCeleb Speaker Recognition Challenge, focusing on diarization on the VoxConverse dataset. Th…
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…
BUT System Description for DIHARD Speech Diarization Challenge 2019
Federico Landini, Shuai Wang, Mireia Diez +8
This paper describes the 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 based on perfo…
End-to-end DNN Based Speaker Recognition Inspired by i-vector and PLDA
Johan Rohdin, Anna Silnova, Mireia Diez +3
Recently several end-to-end speaker verification systems based on deep neural networks (DNNs) have been proposed. These systems have been proven to be competitive for text-dependen…