Speech self-supervised learning has attracted much attention due to its promising
performance in multiple downstream tasks, and has become a new growth engine for …

Self-supervised speech representation learning (speech SSL) has demonstrated the benefit
of scale in learning rich representations for Automatic Speech Recognition (ASR) with …

Fine-tuning of self-supervised models is a powerful transfer learning method in a variety of
fields, including speech processing, since it can utilize generic feature representations …

Self-supervised learning (SSL) for rich speech representations has achieved empirical
success in low-resource Automatic Speech Recognition (ASR) and other speech processing …

Self-supervised pre-training could effectively improve the performance of low-resource
automatic speech recognition (ASR). However, existing self-supervised pre-training are task …

In traditional conversational intelligence from speech, a cascaded pipeline is used, involving
tasks such as voice activity detection, diarization, transcription, and subsequent processing …

In traditional conversational intelligence from speech, a cascaded pipeline is used, involving
tasks such as voice activity detection, diarization, transcription, and subsequent processing …

Instrument playing techniques (IPTs) constitute a pivotal component of musical expression.
However, the development of automatic IPT detection methods suffers from limited labeled …

In this work, several methods have been proposed towards improving the performance of
dialectal automatic speech recognition (ASR). A novel encoder architecture has been …

Recently, self-supervised learning (SSL) techniques have been introduced to solve the
monaural speech enhancement problem. Due to the lack of using clean phase information …