@inproceedings{arora-etal-2025-espnet,
    title = "{ESP}net-{SDS}: Unified Toolkit and Demo for Spoken Dialogue Systems",
    author = "Arora, Siddhant  and
      Peng, Yifan  and
      Shi, Jiatong  and
      Tian, Jinchuan  and
      Chen, William  and
      Bharadwaj, Shikhar  and
      Futami, Hayato  and
      Kashiwagi, Yosuke  and
      Tsunoo, Emiru  and
      Shimizu, Shuichiro  and
      Srivastav, Vaibhav  and
      Watanabe, Shinji",
    editor = "Dziri, Nouha  and
      Ren, Sean (Xiang)  and
      Diao, Shizhe",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.naacl-demo.21/",
    pages = "248--259",
    ISBN = "979-8-89176-191-9",
    abstract = "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."
}