Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …

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 …

This paper presents a novel streaming automatic speech recognition (ASR) framework for
multi-talker overlapping speech captured by a distant microphone array with an arbitrary …

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 …

Guided source separation (GSS) is a type of target-speaker extraction method that relies on
pre-computed speaker activities and blind source separation to perform front-end …

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 multi …

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 ability …

This paper investigates an end-to-end neural diarization (EEND) method for an unknown
number of speakers. In contrast to the conventional cascaded approach to speaker …

This article proposes methods that can optimize a Convolutional BeamFormer (CBF) for
jointly performing denoising, dereverberation, and source separation (DN+ DR+ SS) in a …

This paper is a description of the Speech Technology Center (STC) systems for the CHiME-6
challenge aimed at multimicrophone multi-speaker speech recognition and diarization in a …