1.9k citations · 2k across the 21 of their papers we have counts for
13 papers · 1 filter
Speaker Change Detection for Transformer Transducer ASR
Jian Wu, Zhuo Chen, Min Hu +2
Speaker change detection (SCD) is an important feature that improves the readability of the recognized words from an automatic speech recognition (ASR) system by breaking the word…
Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarization
Dongmei Wang, Xiong Xiao, Naoyuki Kanda +2
This paper describes a speaker diarization model based on target speaker voice activity detection (TS-VAD) using transformers. To overcome the original TS-VAD model's drawback of b…
Streaming Speaker-Attributed ASR with Token-Level Speaker Embeddings
Naoyuki Kanda, Jian Wu, Yu Wu +7
This paper presents a streaming speaker-attributed automatic speech recognition (SA-ASR) model that can recognize ``who spoke what'' with low latency even when multiple people are…
Streaming Multi-Talker ASR with Token-Level Serialized Output Training
Naoyuki Kanda, Jian Wu, Yu Wu +7
This paper proposes a token-level serialized output training (t-SOT), a novel framework for streaming multi-talker automatic speech recognition (ASR). Unlike existing streaming mul…
Separating Long-Form Speech with Group-Wise Permutation Invariant Training
Wangyou Zhang, Zhuo Chen, Naoyuki Kanda +8
Multi-talker conversational speech processing has drawn many interests for various applications such as meeting transcription. Speech separation is often required to handle overlap…
Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR
Naoyuki Kanda, Xiong Xiao, Yashesh Gaur +4
This paper presents Transcribe-to-Diarize, a new approach for neural speaker diarization that uses an end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR). The…
A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio
Naoyuki Kanda, Xiong Xiao, Jian Wu +6
Speaker-attributed automatic speech recognition (SA-ASR) is a task to recognize "who spoke what" from multi-talker recordings. An SA-ASR system usually consists of multiple modules…
Speaker attribution with voice profiles by graph-based semi-supervised learning
Jixuan Wang, Xiong Xiao, Jian Wu +3
Speaker attribution is required in many real-world applications, such as meeting transcription, where speaker identity is assigned to each utterance according to speaker voice prof…
Microsoft Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2020
Xiong Xiao, Naoyuki Kanda, Zhuo Chen +10
This paper describes the Microsoft speaker diarization system for monaural multi-talker recordings in the wild, evaluated at the diarization track of the VoxCeleb Speaker Recogniti…
Speaker diarization with session-level speaker embedding refinement using graph neural networks
Jixuan Wang, Xiong Xiao, Jian Wu +3
Deep speaker embedding models have been commonly used as a building block for speaker diarization systems; however, the speaker embedding model is usually trained according to a gl…
Advances in Online Audio-Visual Meeting Transcription
Takuya Yoshioka, Igor Abramovski, Cem Aksoylar +23
This paper describes a system that generates speaker-annotated transcripts of meetings by using a microphone array and a 360-degree camera. The hallmark of the system is its abilit…
Low-Latency Speaker-Independent Continuous Speech Separation
Takuya Yoshioka, Zhuo Chen, Changliang Liu +3
Speaker independent continuous speech separation (SI-CSS) is a task of converting a continuous audio stream, which may contain overlapping voices of unknown speakers, into a fixed…
Recognizing Overlapped Speech in Meetings: A Multichannel Separation Approach Using Neural Networks
Takuya Yoshioka, Hakan Erdogan, Zhuo Chen +2
The goal of this work is to develop a meeting transcription system that can recognize speech even when utterances of different speakers are overlapped. While speech overlaps have b…