Publications (7)
Advancing Jailbreak Strategies: A Hybrid Approach to Exploiting LLM Vulnerabilities and Bypassing Modern Defenses
Mohamed Ahmed, Mohamed Abdelmouty, Mingyu Kim +3
The advancement of Pre-Trained Language Models (PTLMs) and Large Language Models (LLMs) has led to their widespread adoption across diverse applications. Despite their success, the…
Locale Encoding For Scalable Multilingual Keyword Spotting Models
Pai Zhu, Hyun Jin Park, Alex Park +2
A Multilingual Keyword Spotting (KWS) system detects spokenkeywords over multiple locales. Conventional monolingual KWSapproaches do not scale well to multilingual scenarios becaus…
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy
Sankaran Panchapagesan, Arun Narayanan, Turaj Zakizadeh Shabestary +5
Acoustic Echo Cancellation (AEC) is essential for accurate recognition of queries spoken to a smart speaker that is playing out audio. Previous work has shown that a neural AEC mod…
A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer And Large Scale Synthetic Data
Nathan Howard, Alex Park, Turaj Zakizadeh Shabestary +2
We consider the problem of recognizing speech utterances spoken to a device which is generating a known sound waveform; for example, recognizing queries issued to a digital assista…
Personalizing Keyword Spotting with Speaker Information
Beltrán Labrador, Pai Zhu, Guanlong Zhao +5
Keyword spotting systems often struggle to generalize to a diverse population with various accents and age groups. To address this challenge, we propose a novel approach that integ…
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training
Andrew Hard, Kurt Partridge, Neng Chen +9
We trained a keyword spotting model using federated learning on real user devices and observed significant improvements when the model was deployed for inference on phones. To comp…