457 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of CambridgeGB45 papers
- University of NottinghamGB23 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ21 papers
- Hitachi (Japan)JP13 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR8 papers
- Laboratoire d'Électronique des Technologies de l'InformationFR8 papers
- Donostia International Physics CenterES7 papers
- Hitachi Global Storage Technologies (United States)US7 papers
- CEA GrenobleFR6 papers
- Texas A&M UniversityUS6 papers
- University of ExeterGB6 papers
- Chinese Academy of SciencesCN5 papers
9 papers · 1 filter
Semi-Supervised Training with Pseudo-Labeling for End-to-End Neural Diarization
Yuki Takashima, Yusuke Fujita, Shota Horiguchi +3
In this paper, we present a semi-supervised training technique using pseudo-labeling for end-to-end neural diarization (EEND). The EEND system has shown promising performance compa…
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection
Kota Dohi, Takashi Endo, Harsh Purohit +2
To develop a machine sound monitoring system, a method for detecting anomalous sound is proposed. Exact likelihood estimation using Normalizing Flows is a promising technique for u…
Building Multi lingual TTS using Cross Lingual Voice Conversion
Qinghua Sun, Kenji Nagamatsu
In this paper we propose a new cross-lingual Voice Conversion (VC) approach which can generate all speech parameters (MCEP, LF0, BAP) from one DNN model using PPGs (Phonetic Poster…
Deep Autoencoding GMM-based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-parameter Optimization
Harsh Purohit, Ryo Tanabe, Takashi Endo +3
Failures or breakdowns in factory machinery can be costly to companies, so there is an increasing demand for automatic machine inspection. Existing approaches to acoustic signal-ba…
Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones
Shota Horiguchi, Yusuke Fujita, Kenji Nagamatsu
A novel framework for meeting transcription using asynchronous microphones is proposed in this paper. It consists of audio synchronization, speaker diarization, utterance-wise spee…
Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals
Jing Shi, Xuankai Chang, Pengcheng Guo +5
Neural sequence-to-sequence models are well established for applications which can be cast as mapping a single input sequence into a single output sequence. In this work, we focus…
Speaker-Conditional Chain Model for Speech Separation and Extraction
Jing Shi, Jiaming Xu, Yusuke Fujita +2
Speech separation has been extensively explored to tackle the cocktail party problem. However, these studies are still far from having enough generalization capabilities for real s…
Neural Speaker Diarization with Speaker-Wise Chain Rule
Yusuke Fujita, Shinji Watanabe, Shota Horiguchi +3
Speaker diarization is an essential step for processing multi-speaker audio. Although an end-to-end neural diarization (EEND) method achieved state-of-the-art performance, it is li…
End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors
Shota Horiguchi, Yusuke Fujita, Shinji Watanabe +2
End-to-end speaker diarization for an unknown number of speakers is addressed in this paper. Recently proposed end-to-end speaker diarization outperformed conventional clustering-b…