3 citations · 5 across the 4 of their papers we have counts for
4 papers
GE2E-KWS: Generalized End-to-End Training and Evaluation for Zero-shot Keyword Spotting
Pai Zhu, Jacob W. Bartel, Dhruuv Agarwal +3
We propose GE2E-KWS -- a generalized end-to-end training and evaluation framework for customized keyword spotting. Specifically, enrollment utterances are separated and grouped by…
Adversarial training of Keyword Spotting to Minimize TTS Data Overfitting
Hyun Jin Park, Dhruuv Agarwal, Neng Chen +10
The keyword spotting (KWS) problem requires large amounts of real speech training data to achieve high accuracy across diverse populations. Utilizing large amounts of text-to-speec…
Utilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Model
Hyun Jin Park, Dhruuv Agarwal, Neng Chen +10
This paper explores the use of TTS synthesized training data for KWS (keyword spotting) task while minimizing development cost and time. Keyword spotting models require a huge amou…
Synth4Kws: Synthesized Speech for User Defined Keyword Spotting in Low Resource Environments
Pai Zhu, Dhruuv Agarwal, Jacob W. Bartel +3
One of the challenges in developing a high quality custom keyword spotting (KWS) model is the lengthy and expensive process of collecting training data covering a wide range of lan…