2 citations · 3 across the 3 of their papers we have counts for
9 papers
Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition
Qiujia Li, Chao Zhang, Philip C. Woodland
Commonly used automatic speech recognition (ASR) systems can be classified into frame-synchronous and label-synchronous categories, based on whether the speech is decoded on a per-…
Multi-Task Learning for End-to-End ASR Word and Utterance Confidence with Deletion Prediction
David Qiu, Yanzhang He, Qiujia Li +3
Confidence scores are very useful for downstream applications of automatic speech recognition (ASR) systems. Recent works have proposed using neural networks to learn word or utter…
Learning Word-Level Confidence For Subword End-to-End ASR
David Qiu, Qiujia Li, Yanzhang He +9
We study the problem of word-level confidence estimation in subword-based end-to-end (E2E) models for automatic speech recognition (ASR). Although prior works have proposed trainin…
Residual Energy-Based Models for End-to-End Speech Recognition
Qiujia Li, Yu Zhang, Bo Li +2
End-to-end models with auto-regressive decoders have shown impressive results for automatic speech recognition (ASR). These models formulate the sequence-level probability as a pro…
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech Recognition
Qiujia Li, David Qiu, Yu Zhang +5
For various speech-related tasks, confidence scores from a speech recogniser are a useful measure to assess the quality of transcriptions. In traditional hidden Markov model-based…
Discriminative Neural Clustering for Speaker Diarisation
Qiujia Li, Florian L. Kreyssig, Chao Zhang +1
In this paper, we propose Discriminative Neural Clustering (DNC) that formulates data clustering with a maximum number of clusters as a supervised sequence-to-sequence learning pro…