Howl: A Deployed, Open-Source Wake Word Detection System
Raphael Tang, Jaejun Lee, Afsaneh Razi, Julia Cambre, Ian Bicking, Jofish Kaye, Jimmy Lin
Abstract
We describe Howl, an open-source wake word detection toolkit with native support for open speech datasets such as Mozilla Common Voice (MCV) and Google Speech Commands (GSC). We report benchmark results of various models supported by our toolkit on GSC and our own freely available wake word detection dataset, built from MCV. One of our models is deployed in Firefox Voice, a plugin enabling speech interactivity for the Firefox web browser. Howl represents, to the best of our knowledge, the first fully productionized, open-source wake word detection toolkit with a web browser deployment target. Our codebase is at howl.ai.- Anthology ID:
- 2020.nlposs-1.9
- Volume:
- Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Eunjeong L. Park, Masato Hagiwara, Dmitrijs Milajevs, Nelson F. Liu, Geeticka Chauhan, Liling Tan
- Venue:
- NLPOSS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 61–65
- Language:
- URL:
- https://aclanthology.org/2020.nlposs-1.9
- DOI:
- 10.18653/v1/2020.nlposs-1.9
- Cite (ACL):
- Raphael Tang, Jaejun Lee, Afsaneh Razi, Julia Cambre, Ian Bicking, Jofish Kaye, and Jimmy Lin. 2020. Howl: A Deployed, Open-Source Wake Word Detection System. In Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), pages 61–65, Online. Association for Computational Linguistics.
- Cite (Informal):
- Howl: A Deployed, Open-Source Wake Word Detection System (Tang et al., NLPOSS 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.nlposs-1.9.pdf
- Code
- castorini/howl + additional community code
- Data
- MUSAN, Speech Commands