120 citations · 452 across the 91 of their papers we have counts for
12 papers · 1 filter
On Word Error Rate Definitions and their Efficient Computation for Multi-Speaker Speech Recognition Systems
Thilo von Neumann, Christoph Boeddeker, Keisuke Kinoshita +2
We propose a general framework to compute the word error rate (WER) of ASR systems that process recordings containing multiple speakers at their input and that produce multiple out…
Streaming Target-Speaker ASR with Neural Transducer
Takafumi Moriya, Hiroshi Sato, Tsubasa Ochiai +2
Although recent advances in deep learning technology have boosted automatic speech recognition (ASR) performance in the single-talker case, it remains difficult to recognize multi-…
Analysis of impact of emotions on target speech extraction and speech separation
Ján Švec, Kateřina Žmolíková, Martin Kocour +4
Recently, the performance of blind speech separation (BSS) and target speech extraction (TSE) has greatly progressed. Most works, however, focus on relatively well-controlled condi…
Utterance-by-utterance overlap-aware neural diarization with Graph-PIT
Keisuke Kinoshita, Thilo von Neumann, Marc Delcroix +2
Recent speaker diarization studies showed that integration of end-to-end neural diarization (EEND) and clustering-based diarization is a promising approach for achieving state-of-t…
ConceptBeam: Concept Driven Target Speech Extraction
Yasunori Ohishi, Marc Delcroix, Tsubasa Ochiai +6
We propose a novel framework for target speech extraction based on semantic information, called ConceptBeam. Target speech extraction means extracting the speech of a target speake…
Strategies to Improve Robustness of Target Speech Extraction to Enrollment Variations
Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix +6
Target speech extraction is a technique to extract the target speaker's voice from mixture signals using a pre-recorded enrollment utterance that characterize the voice characteris…
Mask-based Neural Beamforming for Moving Speakers with Self-Attention-based Tracking
Tsubasa Ochiai, Marc Delcroix, Tomohiro Nakatani +1
Beamforming is a powerful tool designed to enhance speech signals from the direction of a target source. Computing the beamforming filter requires estimating spatial covariance mat…
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…
SoundBeam: Target sound extraction conditioned on sound-class labels and enrollment clues for increased performance and continuous learning
Marc Delcroix, Jorge Bennasar Vázquez, Tsubasa Ochiai +3
In many situations, we would like to hear desired sound events (SEs) while being able to ignore interference. Target sound extraction (TSE) tackles this problem by estimating the a…
Tight integration of neural- and clustering-based diarization through deep unfolding of infinite Gaussian mixture model
Keisuke Kinoshita, Marc Delcroix, Tomoharu Iwata
Speaker diarization has been investigated extensively as an important central task for meeting analysis. Recent trend shows that integration of end-to-end neural (EEND)-and cluster…
Learning to Enhance or Not: Neural Network-Based Switching of Enhanced and Observed Signals for Overlapping Speech Recognition
Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix +3
The combination of a deep neural network (DNN) -based speech enhancement (SE) front-end and an automatic speech recognition (ASR) back-end is a widely used approach to implement ov…
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR
Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix +4
It is challenging to improve automatic speech recognition (ASR) performance in noisy conditions with single-channel speech enhancement (SE). In this paper, we investigate the cause…