ESPnet-SDS：面向口语对话系统的统一工具包与演示
ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems
AI总结：
本文提出开源工具包ESPnet-SDS，为级联和端到端口语对话系统构建统一网页界面，并提供延迟、理解能力、响应质量及音频质量等自动化评估指标，通过对比实验揭示当前端到端系统在音频质量和响应多样性上的不足。
摘要：
音频基础模型（FMs）的进步激发了人们对端到端（E2E）口语对话系统的兴趣，但每个系统不同的网页界面使得有效比较和对比它们变得困难。受此启发，我们引入了一个开源、用户友好的工具包，旨在为各种级联和端到端口语对话系统构建统一的网页界面。我们的演示进一步为用户提供了获取即时自动化评估指标的选项，例如（1）延迟，（2）理解用户输入的能力，（3）系统响应的连贯性、多样性和相关性，以及（4）系统输出的可懂度和音频质量。利用这些评估指标，我们以人人对话数据集作为代理，比较了各种级联和端到端口语对话系统。我们的分析表明，该工具包使研究人员能够轻松比较和对比不同技术，提供了有价值的见解，例如当前端到端系统音频质量较差且响应多样性较低。使用我们的工具包生成的一个示例演示在此公开可用：https://huggingface.co/spaces/Siddhant/Voice_Assistant_Demo。
英文摘要：
Advancements in audio foundation models (FMs) have fueled interest in end-to-end (E2E) spoken dialogue systems, but different web interfaces for each system makes it challenging to compare and contrast them effectively. Motivated by this, we introduce an open-source, user-friendly toolkit designed to build unified web interfaces for various cascaded and E2E spoken dialogue systems. Our demo further provides users with the option to get on-the-fly automated evaluation metrics such as (1) latency, (2) ability to understand user input, (3) coherence, diversity, and relevance of system response, and (4) intelligibility and audio quality of system output. Using the evaluation metrics, we compare various cascaded and E2E spoken dialogue systems with a human-human conversation dataset as a proxy. Our analysis demonstrates that the toolkit allows researchers to effortlessly compare and contrast different technologies, providing valuable insights such as current E2E systems having poorer audio quality and less diverse responses. An example demo produced using our toolkit is publicly available here: https://huggingface.co/spaces/Siddhant/Voice_Assistant_Demo.
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。
