4 papers
The Universal Personalizer: Few-Shot Dysarthric Speech Recognition via Meta-Learning
Dhruuv Agarwal, Harry Zhang, Yang Yu +1
Personalizing dysarthric ASR is hindered by demanding enrollment collection and per-user training. We propose a hybrid meta-training method for a single model, enabling zero-shot a…
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…