Fetching the paper…
Reading the bibliography…
Multilingual intelligent assistants, such as ChatGPT, have recently gained popularity.
“Librispeech: an asr corpus based on public domain audio books,”
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur, · 2015
Earlier work this paper cites.
“An open/free database and benchmark for uyghur speaker recognition,”
Askar Rozi, Dong Wang, Zhiyong Zhang, and Thomas Fang Zheng, · 2015
Earlier work this paper cites.
“Language independent end-to-end architecture for joint language identification and speech recognition,”
Shinji Watanabe, Takaaki Hori, and John R Hershey, · 2017
Earlier work this paper cites.
“Aishell-1: An open-source mandarin speech corpus and a speech recognition baseline,”
Hui Bu, Jiayu Du, Xingyu Na, Bengu Wu, and Hao Zheng, · 2017
Earlier work this paper cites.
“Multilingual speech recognition with a single end-to-end model,”
Shubham Toshniwal, Tara N Sainath, Ron J Weiss, Bo Li, Pedro Moreno, Eugene Weinstein, and Kanishka Rao, · 2018
Earlier work this paper cites.
“Large-scale multilingual speech recognition with a streaming end-to-end model,”
Anjuli Kannan, Arindrima Datta, Tara N Sainath, Eugene Weinstein, Bhuvana Ramabhadran, Yonghui Wu, Ankur Bapna, Zhifeng Chen, and Seungji Lee, · 2019
Earlier work this paper cites.
“Parameter-efficient transfer learning for nlp,”
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly, · 2019
Cited alongside, same era.
“Common voice: A massively-multilingual speech corpus,”
Rosana Ardila, Megan Branson, Kelly Davis, Michael Henretty, Michael Kohler, Josh Meyer, Reuben Morais, Lindsay Saunders, Francis M Tyers, and Gregor Weber, · 2019
Cited alongside, same era.
“Massively multilingual asr: 50 languages, 1 model, 1 billion parameters,”
Vineel Pratap, Anuroop Sriram, Paden Tomasello, Awni Hannun, Vitaliy Liptchinsky, Gabriel Synnaeve, and Ronan Collobert, · 2020
Cited alongside, same era.
“Streaming end-to-end bilingual asr systems with joint language identification,”
Surabhi Punjabi, Harish Arsikere, Zeynab Raeesy, Chander Chandak, Nikhil Bhave, Ankish Bansal, Markus Müller, Sergio Murillo, Ariya Rastrow, Sri Garimella, et al., · 2020
Cited alongside, same era.
“The power of scale for parameter-efficient prompt tuning,”
Brian Lester, Rami Al-Rfou, and Noah Constant, · 2021
Later among the works it cites.
“Prefix-tuning: Optimizing continuous prompts for generation,”
Xiang Lisa Li and Percy Liang, · 2021
Later among the works it cites.
Shinnosuke Takamichi, Ludwig Kürzinger, Takaaki Saeki, Sayaka Shiota, and Shinji Watanabe, · 2021
Later among the works it cites.
“Streaming end-to-end multilingual speech recognition with joint language identification,”
Chao Zhang, Bo Li, Tara Sainath, Trevor Strohman, Sepand Mavandadi, Shuo-yiin Chang, and Parisa Haghani, · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, and Michael Auli, · 2020
Cited alongside, same era.
“An open speech resource for tibetan multi-dialect and multitask recognition,”
Yue Zhao, Xiaona Xu, Jianjian Yue, Wei Song, Xiali Li, Licheng Wu, and Qiang Ji, · 2020
Cited alongside, same era.
Binbin Zhang, Hang Lv, Pengcheng Guo, Qijie Shao, Chao Yang, Lei Xie, Xin Xu, Hui Bu, Xiaoyu Chen, Chenchen Zeng, et al., · 2022
Later among the works it cites.
“Mole: Mixture of language experts for multi-lingual automatic speech recognition,”
Yoohwan Kwon and Soo-Whan Chung, · 2023
Closest in time.