research
∙
09/09/2023
Leveraging Large Language Models for Exploiting ASR Uncertainty
While large language models excel in a variety of natural language proce...
share
research
∙
10/21/2022
Audio-to-Intent Using Acoustic-Textual Subword Representations from End-to-End ASR
Accurate prediction of the user intent to interact with a voice assistan...
research
∙
03/30/2022
Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models
We address the problem of detecting speech directed to a device that doe...
research
∙
10/09/2021
Streaming on-device detection of device directed speech from voice and touch-based invocation
When interacting with smart devices such as mobile phones or wearables, ...
research
∙
05/14/2021
Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation
We present a unified and hardware efficient architecture for two stage v...
research
∙
10/20/2020
Knowledge Transfer for Efficient On-device False Trigger Mitigation
In this paper, we address the task of determining whether a given uttera...
research
∙
08/18/2020
Complementary Language Model and Parallel Bi-LRNN for False Trigger Mitigation
False triggers in voice assistants are unintended invocations of the ass...
research
∙
01/25/2020
Lattice-based Improvements for Voice Triggering Using Graph Neural Networks
Voice-triggered smart assistants often rely on detection of a trigger-ph...
research
∙
08/29/2017
Information Theoretic Analysis of DNN-HMM Acoustic Modeling
We propose an information theoretic framework for quantitative assessmen...
research
∙
10/18/2016
Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models
Conventional deep neural networks (DNN) for speech acoustic modeling rel...
research
∙
01/22/2016
