1 citations · 2 across the 9 of their papers we have counts for
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Fast and accurate factorized neural transducer for text adaption of end-to-end speech recognition models
Rui Zhao, Jian Xue, Partha Parthasarathy +2
Neural transducer is now the most popular end-to-end model for speech recognition, due to its naturally streaming ability. However, it is challenging to adapt it with text-only dat…
Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition
Yashesh Gaur, Nick Kibre, Jian Xue +5
Automatic Speech Recognition (ASR) systems typically yield output in lexical form. However, humans prefer a written form output. To bridge this gap, ASR systems usually employ Inve…
LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers
Peidong Wang, Eric Sun, Jian Xue +5
Automatic speech recognition (ASR) and speech translation (ST) can both use neural transducers as the model structure. It is thus possible to use a single transducer model to perfo…
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability
Jian Xue, Peidong Wang, Jinyu Li +1
In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target l…
Large-Scale Streaming End-to-End Speech Translation with Neural Transducers
Jian Xue, Peidong Wang, Jinyu Li +2
Neural transducers have been widely used in automatic speech recognition (ASR). In this paper, we introduce it to streaming end-to-end speech translation (ST), which aims to conver…