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
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.nlposs-1.9.pdf
Video:
 https://slideslive.com/38939746
Code
 castorini/howl +  additional community code
Data
MUSANSpeech Commands