120 citations · 452 across the 91 of their papers we have counts for
16 papers · 1 filter
Attention-based Multi-hypothesis Fusion for Speech Summarization
Takatomo Kano, Atsunori Ogawa, Marc Delcroix +1
Speech summarization, which generates a text summary from speech, can be achieved by combining automatic speech recognition (ASR) and text summarization (TS). With this cascade app…
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…
SA-SDR: A novel loss function for separation of meeting style data
Thilo von Neumann, Keisuke Kinoshita, Christoph Boeddeker +2
Many state-of-the-art neural network-based source separation systems use the averaged Signal-to-Distortion Ratio (SDR) as a training objective function. The basic SDR is, however,…
Speeding Up Permutation Invariant Training for Source Separation
Thilo von Neumann, Christoph Boeddeker, Keisuke Kinoshita +2
Permutation invariant training (PIT) is a widely used training criterion for neural network-based source separation, used for both utterance-level separation with utterance-level P…
Graph-PIT: Generalized permutation invariant training for continuous separation of arbitrary numbers of speakers
Thilo von Neumann, Keisuke Kinoshita, Christoph Boeddeker +2
Automatic transcription of meetings requires handling of overlapped speech, which calls for continuous speech separation (CSS) systems. The uPIT criterion was proposed for utteranc…
Few-shot learning of new sound classes for target sound extraction
Marc Delcroix, Jorge Bennasar Vázquez, Tsubasa Ochiai +2
Target sound extraction consists of extracting the sound of a target acoustic event (AE) class from a mixture of AE sounds. It can be realized using a neural network that extracts…
PILOT: Introducing Transformers for Probabilistic Sound Event Localization
Christopher Schymura, Benedikt Bönninghoff, Tsubasa Ochiai +5
Sound event localization aims at estimating the positions of sound sources in the environment with respect to an acoustic receiver (e.g. a microphone array). Recent advances in thi…
Should We Always Separate?: Switching Between Enhanced and Observed Signals for Overlapping Speech Recognition
Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix +3
Although recent advances in deep learning technology improved automatic speech recognition (ASR), it remains difficult to recognize speech when it overlaps other people's voices. S…
Advances in integration of end-to-end neural and clustering-based diarization for real conversational speech
Keisuke Kinoshita, Marc Delcroix, Naohiro Tawara
Recently, we proposed a novel speaker diarization method called End-to-End-Neural-Diarization-vector clustering (EEND-vector clustering) that integrates clustering-based and end-to…
Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization
Christopher Schymura, Tsubasa Ochiai, Marc Delcroix +4
Sound event localization frameworks based on deep neural networks have shown increased robustness with respect to reverberation and noise in comparison to classical parametric appr…
Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain
Julio Wissing, Benedikt Boenninghoff, Dorothea Kolossa +6
Estimating the positions of multiple speakers can be helpful for tasks like automatic speech recognition or speaker diarization. Both applications benefit from a known speaker posi…
Dual-Path Modeling for Long Recording Speech Separation in Meetings
Chenda Li, Zhuo Chen, Yi Luo +6
The continuous speech separation (CSS) is a task to separate the speech sources from a long, partially overlapped recording, which involves a varying number of speakers. A straight…
End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend
Wangyou Zhang, Christoph Boeddeker, Shinji Watanabe +7
Recently, the end-to-end approach has been successfully applied to multi-speaker speech separation and recognition in both single-channel and multichannel conditions. However, seve…
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…
Multimodal Attention Fusion for Target Speaker Extraction
Hiroshi Sato, Tsubasa Ochiai, Keisuke Kinoshita +3
Target speaker extraction, which aims at extracting a target speaker's voice from a mixture of voices using audio, visual or locational clues, has received much interest. Recently…
Neural Network-based Virtual Microphone Estimator
Tsubasa Ochiai, Marc Delcroix, Tomohiro Nakatani +3
Developing microphone array technologies for a small number of microphones is important due to the constraints of many devices. One direction to address this situation consists of…