Can I read ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit on EtoBox?

ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit by Yan, Brian; Shi, Jiatong; Tang, Yun; Inaguma, Hirofumi; Peng, Yifan; Dalmia, Siddharth; Polák, Peter; Fernandes, Patrick; Berrebbi, Dan; Hayashi, Tomoki; Zhang, Xiaohui; Ni, Zhaoheng; Hira, Moto; Maiti, Soumi; Pino, Juan; Watanabe, Shinji is a scholarly article available to read on EtoBox.

What is ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit about?

ESPnet-ST-v2 is a revamp of the open-source ESPnet-ST toolkit necessitated by the broadening interests of the spoken language translation community. ESPnet-ST-v2 supports 1) offline speech-to-text translation (ST), 2) simultaneous speech-to-text translation (SST), and 3) offline speech-to-speech translation (S2ST) -- each task is supported with a wide variety of approaches, differentiating ESPnet-ST-v2 from other open source spoken language translation toolkits. This toolkit offers state-of-the-art architectures such as transducers, hybrid CTC/attention, multi-decoders with searchable intermediates, time-synchronous blockwise CTC/attention, Translatotron models, and direct discrete unit models. In this paper, we describe the overall design, example models for each task, and performance benchmarking behind ESPnet-ST-v2, which is publicly available at https://github.com/espnet/espnet.

Author

Yan, Brian; Shi, Jiatong; Tang, Yun; Inaguma, Hirofumi; Peng, Yifan; Dalmia, Siddharth; Polák, Peter; Fernandes, Patrick; Berrebbi, Dan; Hayashi, Tomoki; Zhang, Xiaohui; Ni, Zhaoheng; Hira, Moto; Maiti, Soumi; Pino, Juan; Watanabe, Shinji

Published

2023

Language

EN