Unified Modeling of Multi-Domain Multi-Device ASR Systems

no code implementations • 13 May 2022 • Soumyajit Mitra, Swayambhu Nath Ray, Bharat Padi, Arunasish Sen, Raghavendra Bilgi, Harish Arsikere, Shalini Ghosh, Ajay Srinivasamurthy, Sri Garimella

Modern Automatic Speech Recognition (ASR) systems often use a portfolio of domain-specific models in order to get high accuracy for distinct user utterance types across different devices.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Improving RNN-T ASR Performance with Date-Time and Location Awareness

no code implementations • 11 Jun 2021 • Swayambhu Nath Ray, Soumyajit Mitra, Raghavendra Bilgi, Sri Garimella

In this paper, we explore the benefits of incorporating context into a Recurrent Neural Network (RNN-T) based Automatic Speech Recognition (ASR) model to improve the speech recognition for virtual assistants.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End

no code implementations • 14 May 2021 • Swayambhu Nath Ray, Minhua Wu, Anirudh Raju, Pegah Ghahremani, Raghavendra Bilgi, Milind Rao, Harish Arsikere, Ariya Rastrow, Andreas Stolcke, Jasha Droppo

On the other hand, a streaming system using per-frame intent posteriors as extra inputs for the RNN-T ASR system yields a 3. 33% relative WERR.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1