2 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
Prompt-tuning in ASR systems for efficient domain-adaptation
Saket Dingliwal, Ashish Shenoy, Sravan Bodapati +3
Automatic Speech Recognition (ASR) systems have found their use in numerous industrial applications in very diverse domains. Since domain-specific systems perform better than their…
Towards Continual Entity Learning in Language Models for Conversational Agents
Ravi Teja Gadde, Ivan Bulyko
Neural language models (LM) trained on diverse corpora are known to work well on previously seen entities, however, updating these models with dynamically changing entities such as…
Neural Composition: Learning to Generate from Multiple Models
Denis Filimonov, Ravi Teja Gadde, Ariya Rastrow
Decomposing models into multiple components is critically important in many applications such as language modeling (LM) as it enables adapting individual components separately and…
Training Neural Speech Recognition Systems with Synthetic Speech Augmentation
Jason Li, Ravi Gadde, Boris Ginsburg +1
Building an accurate automatic speech recognition (ASR) system requires a large dataset that contains many hours of labeled speech samples produced by a diverse set of speakers. Th…