2 papers
cs.CL2022
Audio-to-Intent Using Acoustic-Textual Subword Representations from End-to-End ASR
Pranay Dighe, Prateeth Nayak, Oggi Rudovic +3
Accurate prediction of the user intent to interact with a voice assistant (VA) on a device (e.g. on the phone) is critical for achieving naturalistic, engaging, and privacy-centric…
eess.AS2020
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…