2 citations · 2 across the 3 of their papers we have counts for
7 papers
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…
Remember the context! ASR slot error correction through memorization
Dhanush Bekal, Ashish Shenoy, Monica Sunkara +2
Accurate recognition of slot values such as domain specific words or named entities by automatic speech recognition (ASR) systems forms the core of the Goal-oriented Dialogue Syste…
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…
Best of Both Worlds: Robust Accented Speech Recognition with Adversarial Transfer Learning
Nilaksh Das, Sravan Bodapati, Monica Sunkara +2
Training deep neural networks for automatic speech recognition (ASR) requires large amounts of transcribed speech. This becomes a bottleneck for training robust models for accented…
Neural Inverse Text Normalization
Monica Sunkara, Chaitanya Shivade, Sravan Bodapati +1
While there have been several contributions exploring state of the art techniques for text normalization, the problem of inverse text normalization (ITN) remains relatively unexplo…
Multimodal Semi-supervised Learning Framework for Punctuation Prediction in Conversational Speech
Monica Sunkara, Srikanth Ronanki, Dhanush Bekal +2
In this work, we explore a multimodal semi-supervised learning approach for punctuation prediction by learning representations from large amounts of unlabelled audio and text data.…