16 citations · 19 across the 5 of their papers we have counts for
9 papers
Token-level Speaker Change Detection Using Speaker Difference and Speech Content via Continuous Integrate-and-fire
Zhiyun Fan, Zhenlin Liang, Linhao Dong +6
In multi-talker scenarios such as meetings and conversations, speech processing systems are usually required to segment the audio and then transcribe each segmentation. These two s…
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection
Minglun Han, Linhao Dong, Zhenlin Liang +4
Nowadays, most methods in end-to-end contextual speech recognition bias the recognition process towards contextual knowledge. Since all-neural contextual biasing methods rely on ph…
CIF-based Collaborative Decoding for End-to-end Contextual Speech Recognition
Minglun Han, Linhao Dong, Shiyu Zhou +1
End-to-end (E2E) models have achieved promising results on multiple speech recognition benchmarks, and shown the potential to become the mainstream. However, the unified structure…
A Comparison of Label-Synchronous and Frame-Synchronous End-to-End Models for Speech Recognition
Linhao Dong, Cheng Yi, Jianzong Wang +4
End-to-end models are gaining wider attention in the field of automatic speech recognition (ASR). One of their advantages is the simplicity of building that directly recognizes the…
CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition
Linhao Dong, Bo Xu
In this paper, we propose a novel soft and monotonic alignment mechanism used for sequence transduction. It is inspired by the integrate-and-fire model in spiking neural networks a…
Self-Attention Aligner: A Latency-Control End-to-End Model for ASR Using Self-Attention Network and Chunk-Hopping
Linhao Dong, Feng Wang, Bo Xu
Self-attention network, an attention-based feedforward neural network, has recently shown the potential to replace recurrent neural networks (RNNs) in a variety of NLP tasks. Howev…