Defect detection is a key element of quality control in today's industries, and the process
requires the incorporation of automated methods, including image sensors, to detect any …

Benefiting from massive and diverse data sources, speech foundation models exhibit strong
generalization and knowledge transfer capabilities to a wide range of downstream tasks …

Self-supervised learning (SSL) based speech pre-training has attracted much attention for
its capability of extracting rich representations learned from massive unlabeled data. On the …

It has been shown that the intelligibility of noisy speech can be improved by speech
enhancement (SE) algorithms. However, monaural SE has not been established as an …

In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is
capable of transcribing, recognizing, and separating multiple musical instruments from an …

Lately, the development of deep learning algorithms has marked milestones in the field of
speech processing. In particular, the release of pre-trained feature extraction models has …

It has been shown that the intelligibility of noisy speech can be improved by speech
enhancement algorithms. However, speech enhancement has not been established as an …

The Streaming Unmixing and Recognition Transducer (SURT) model was proposed recently
as an end-to-end approach for continuous, streaming, multi-talker speech recognition (ASR) …

Distant-microphone meeting transcription is a challenging task. State-of-the-art end-to-end
speaker-attributed automatic speech recognition (SA-ASR) architectures lack a multichannel …

Speech separation remains a vital area of research for many modern technologies. The
ubiquitous spread of deep neural networks (DNNs) in many areas of signal processing (SP) …