4 papers
LLM-Synth4KWS: Scalable Automatic Generation and Synthesis of Confusable Data for Custom Keyword Spotting
Pai Zhu, Quan Wang, Dhruuv Agarwal +1
Custom keyword spotting (KWS) allows detecting user-defined spoken keywords from streaming audio. This is achieved by comparing the embeddings from voice enrollments and input audi…
GraphemeAug: A Systematic Approach to Synthesized Hard Negative Keyword Spotting Examples
Harry Zhang, Kurt Partridge, Pai Zhu +4
Spoken Keyword Spotting (KWS) is the task of distinguishing between the presence and absence of a keyword in audio. The accuracy of a KWS model hinges on its ability to correctly c…
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…