37 citations · 58 across the 7 of their papers we have counts for
7 papers
Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition
Yash Jain, David Chan, Pranav Dheram +4
Recent advances in machine learning have demonstrated that multi-modal pre-training can improve automatic speech recognition (ASR) performance compared to randomly initialized mode…
Turn-taking and Backchannel Prediction with Acoustic and Large Language Model Fusion
Jinhan Wang, Long Chen, Aparna Khare +6
We propose an approach for continuous prediction of turn-taking and backchanneling locations in spoken dialogue by fusing a neural acoustic model with a large language model (LLM).…
Mining Duplicate Questions of Stack Overflow
Mihir Kale, Anirudha Rayasam, Radhika Parik +1
There has a been a significant rise in the use of Community Question Answering sites (CQAs) over the last decade owing primarily to their ability to leverage the wisdom of the crow…
Toward Fairness in Speech Recognition: Discovery and mitigation of performance disparities
Pranav Dheram, Murugesan Ramakrishnan, Anirudh Raju +6
As for other forms of AI, speech recognition has recently been examined with respect to performance disparities across different user cohorts. One approach to achieve fairness in s…
On joint training with interfaces for spoken language understanding
Anirudh Raju, Milind Rao, Gautam Tiwari +6
Spoken language understanding (SLU) systems extract both text transcripts and semantics associated with intents and slots from input speech utterances. SLU systems usually consist…
Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding
Milind Rao, Pranav Dheram, Gautam Tiwari +4
Spoken language understanding (SLU) systems extract transcriptions, as well as semantics of intent or named entities from speech, and are essential components of voice activated sy…
Speech To Semantics: Improve ASR and NLU Jointly via All-Neural Interfaces
Milind Rao, Anirudh Raju, Pranav Dheram +2
We consider the problem of spoken language understanding (SLU) of extracting natural language intents and associated slot arguments or named entities from speech that is primarily…