An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement

27 February 2024

Papers citing "An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement"

7 / 7 papers shown

Title
MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition Xiaohuan Zhou Jiaming Wang Zeyu Cui Shiliang Zhang Zhijie Yan Jingren Zhou Chang Zhou 74 12 0 29 Nov 2022
Reducing Language confusion for Code-switching Speech Recognition with Token-level Language Diarization Hexin Liu Haihua Xu Leibny Paola García Andy W. H. Khong Yi He Sanjeev Khudanpur 51 25 0 26 Oct 2022
Integrating Knowledge in End-to-End Automatic Speech Recognition for Mandarin-English Code-Switching Chia-Yu Li Ngoc Thang Vu 53 12 0 19 Dec 2021
Transformer-Transducers for Code-Switched Speech Recognition Siddharth Dalmia Yuzong Liu S. Ronanki Katrin Kirchhoff 71 47 0 30 Nov 2020
Self-training and Pre-training are Complementary for Speech Recognition Qiantong Xu Alexei Baevski Tatiana Likhomanenko Paden Tomasello Alexis Conneau R. Collobert Gabriel Synnaeve Michael Auli SSL VLM 137 173 0 22 Oct 2020
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition Yu Zhang James Qin Daniel S. Park Wei Han Chung-Cheng Chiu Ruoming Pang Quoc V. Le Yonghui Wu VLM SSL 215 310 0 20 Oct 2020
The ASRU 2019 Mandarin-English Code-Switching Speech Recognition Challenge: Open Datasets, Tracks, Methods and Results Xian Shi Qiangze Feng Lei Xie 42 47 0 12 Jul 2020