most citedASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2021

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…

eess.AS2021

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…

eess.AS20214 cited

ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling

Ashish Shenoy, Sravan Bodapati, Katrin Kirchhoff

Automatic Speech Recognition (ASR) robustness toward slot entities are critical in e-commerce voice assistants that involve monetary transactions and purchases. Along with effectiv…

cs.CL2021

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…

cs.CL2021

Contextual Biasing of Language Models for Speech Recognition in Goal-Oriented Conversational Agents

Ashish Shenoy, Sravan Bodapati, Katrin Kirchhoff

Goal-oriented conversational interfaces are designed to accomplish specific tasks and typically have interactions that tend to span multiple turns adhering to a pre-defined structu…