24 citations · 35 across the 14 of their papers we have counts for
6 papers · 1 filter
Device-Directed Speech Detection for Follow-up Conversations Using Large Language Models
Ognjen, Rudovic, Pranay Dighe +7
Follow-up conversations with virtual assistants (VAs) enable a user to seamlessly interact with a VA without the need to repeatedly invoke it using a keyword (after the first query…
Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models
Vineet Garg, Ognjen Rudovic, Pranay Dighe +5
We address the problem of detecting speech directed to a device that does not contain a specific wake-word. Specifically, we focus on audio coming from a touch-based invocation. Mi…
Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation
Vineet Garg, Wonil Chang, Siddharth Sigtia +4
We present a unified and hardware efficient architecture for two stage voice trigger detection (VTD) and false trigger mitigation (FTM) tasks. Two stage VTD systems of voice assist…
Knowledge Transfer for Efficient On-device False Trigger Mitigation
Pranay Dighe, Erik Marchi, Srikanth Vishnubhotla +2
In this paper, we address the task of determining whether a given utterance is directed towards a voice-enabled smart-assistant device or not. An undirected utterance is termed as…
Complementary Language Model and Parallel Bi-LRNN for False Trigger Mitigation
Rishika Agarwal, Xiaochuan Niu, Pranay Dighe +3
False triggers in voice assistants are unintended invocations of the assistant, which not only degrade the user experience but may also compromise privacy. False trigger mitigation…
Lattice-based Improvements for Voice Triggering Using Graph Neural Networks
Pranay Dighe, Saurabh Adya, Nuoyu Li +6
Voice-triggered smart assistants often rely on detection of a trigger-phrase before they start listening for the user request. Mitigation of false triggers is an important aspect o…