8 papers
Optimize what matters: Training DNN-HMM Keyword Spotting Model Using End Metric
Ashish Shrivastava, Arnav Kundu, Chandra Dhir +2
Deep Neural Network--Hidden Markov Model (DNN-HMM) based methods have been successfully used for many always-on keyword spotting algorithms that detect a wake word to trigger a dev…
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…
On the Role of Visual Cues in Audiovisual Speech Enhancement
Zakaria Aldeneh, Anushree Prasanna Kumar, Barry-John Theobald +4
We present an introspection of an audiovisual speech enhancement model. In particular, we focus on interpreting how a neural audiovisual speech enhancement model uses visual cues t…
Detecting Emotion Primitives from Speech and their use in discerning Categorical Emotions
Vasudha Kowtha, Vikramjit Mitra, Chris Bartels +5
Emotion plays an essential role in human-to-human communication, enabling us to convey feelings such as happiness, frustration, and sincerity. While modern speech technologies rely…
Multi-task Learning for Speaker Verification and Voice Trigger Detection
Siddharth Sigtia, Erik Marchi, Sachin Kajarekar +2
Automatic speech transcription and speaker recognition are usually treated as separate tasks even though they are interdependent. In this study, we investigate training a single ne…