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Zero-resource Speech Translation and Recognition with LLMs
Karel Mundnich, Xing Niu, Prashant Mathur +10
Despite recent advancements in speech processing, zero-resource speech translation (ST) and automatic speech recognition (ASR) remain challenging problems. In this work, we propose…
Device Directedness with Contextual Cues for Spoken Dialog Systems
Dhanush Bekal, Sundararajan Srinivasan, Sravan Bodapati +2
In this work, we define barge-in verification as a supervised learning task where audio-only information is used to classify user spoken dialogue into true and false barge-ins. Fol…
Towards Personalization of CTC Speech Recognition Models with Contextual Adapters and Adaptive Boosting
Saket Dingliwal, Monica Sunkara, Sravan Bodapati +3
End-to-end speech recognition models trained using joint Connectionist Temporal Classification (CTC)-Attention loss have gained popularity recently. In these models, a non-autoregr…
Adapting Long Context NLM for ASR Rescoring in Conversational Agents
Ashish Shenoy, Sravan Bodapati, Monica Sunkara +2
Neural Language Models (NLM), when trained and evaluated with context spanning multiple utterances, have been shown to consistently outperform both conventional n-gram language mod…
Transformer-Transducers for Code-Switched Speech Recognition
Siddharth Dalmia, Yuzong Liu, Srikanth Ronanki +1
We live in a world where 60% of the population can speak two or more languages fluently. Members of these communities constantly switch between languages when having a conversation…
Robust Prediction of Punctuation and Truecasing for Medical ASR
Monica Sunkara, Srikanth Ronanki, Kalpit Dixit +2
Automatic speech recognition (ASR) systems in the medical domain that focus on transcribing clinical dictations and doctor-patient conversations often pose many challenges due to t…