ESPnet-ST-v2：多用途口语翻译工具包
ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit
AI总结：
ESPnet-ST-v2 是一个多用途开源口语翻译工具包，支持离线语音到文本翻译、同声传译和语音到语音翻译，并提供多种最先进架构与性能基准。
摘要：
ESPnet-ST-v2 是对开源 ESPnet-ST 工具包的一次全面革新，这一革新源于口语翻译社区日益广泛的兴趣。ESPnet-ST-v2 支持 1) 离线语音到文本翻译（ST）、2) 同声传译语音到文本翻译（SST）以及 3) 离线语音到语音翻译（S2ST）——每项任务都得到了多种方法的支持，这使得 ESPnet-ST-v2 与其他开源口语翻译工具包区别开来。该工具包提供了最先进的架构，例如 transducer、混合 CTC/注意力、具有可搜索中间表示的多解码器、时间同步分块 CTC/注意力、Translatotron 模型以及直接离散单元模型。在本文中，我们描述了 ESPnet-ST-v2 背后的整体设计、每项任务的示例模型以及性能基准测试，该工具包已在 https://github.com/espnet/espnet 上公开发布。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
