Non-autoregressive (NAR) generation, which is first proposed in neural machine translation
(NMT) to speed up inference, has attracted much attention in both machine learning and …

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

Although automatic speech recognition (ASR) can perform well in common non-overlapping
environments, sustaining performance in multi-talker overlapping speech recognition …

Continuous integrate-and-fire (CIF) based models, which use a soft and monotonic
alignment mechanism, have been well applied in non-autoregressive (NAR) speech …

The recently proposed serialized output training (SOT) simplifies multi-talker automatic
speech recognition (ASR) by generating speaker transcriptions separated by a special …

Non-autoregressive end-to-end ASR framework might be potentially appropriate for code-
switching recognition task thanks to its inherent property that present output token being …

We propose CONF-TSASR, a non-autoregressive end-to-end time-frequency domain
architecture for single-channel target-speaker automatic speech recognition (TS-ASR). The …

Self-supervised learning leverages unlabeled data effectively, improving label efficiency and
generalization to domains without labeled data. While recent work has studied …

We present an end-to-end multichannel speaker-attributed automatic speech recognition
(MC-SA-ASR) system that combines a Conformer-based encoder with multi-frame cross …

Joint modeling of multi-speaker ASR and speaker diarization has recently shown promising
results in speaker-attributed automatic speech recognition (SA-ASR). Although being able to …