Abstract Machine learning methods are extensively used for processing and analysing
speech signals by virtue of their performance gains over multiple domains. Deep learning …

Self-supervised learning (SSL) achieves great success in speech recognition, while limited
exploration has been attempted for other speech processing tasks. As speech signal …

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …

This article is a survey of deep learning methods for single and multiple sound source
localization, with a focus on sound source localization in indoor environments, where …

This report describes our submission to the track 1 and track 2 of the VoxCeleb Speaker
Recognition Challenge 2021 (VoxSRC 2021). Both track 1 and track 2 share the same …

Learning robust speaker embeddings is a crucial step in speaker diarization. Deep neural
networks can accurately capture speaker discriminative characteristics and popular deep …

Recent development of speech signal processing, such as speech recognition, speaker
diarization, etc., has inspired numerous applications of speech technologies. The meeting …

We performed an experimental review of current diarization systems for the conversational
telephone speech (CTS) domain. In detail, we considered a total of eight different algorithms …

pyannote. audio is an open-source toolkit written in Python for speaker diarization. Version
2.1 introduces a major overhaul of pyannote. audio default speaker diarization pipeline …

In this paper, we present a novel speaker diarization system for streaming on-device
applications. In this system, we use a transformer transducer to detect the speaker turns …