26 citations · 63 across the 11 of their papers we have counts for
15 papers
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…
Improving Voice Trigger Detection with Metric Learning
Prateeth Nayak, Takuya Higuchi, Anmol Gupta +9
Voice trigger detection is an important task, which enables activating a voice assistant when a target user speaks a keyword phrase. A detector is typically trained on speech data…
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…
CALM: Contrastive Aligned Audio-Language Multirate and Multimodal Representations
Vin Sachidananda, Shao-Yen Tseng, Erik Marchi +2
Deriving multimodal representations of audio and lexical inputs is a central problem in Natural Language Understanding (NLU). In this paper, we present Contrastive Aligned Audio-La…
Whispered and Lombard Neural Speech Synthesis
Qiong Hu, Tobias Bleisch, Petko Petkov +3
It is desirable for a text-to-speech system to take into account the environment where synthetic speech is presented, and provide appropriate context-dependent output to the user.…
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…