activity
20162021
most citedLingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

184 citations · 289 across the 10 of their papers we have counts for

collaborators

17 papers

cs.CL20218 cited

Language model fusion for streaming end to end speech recognition

Rodrigo Cabrera, Xiaofeng Liu, Mohammadreza Ghodsi +3

Streaming processing of speech audio is required for many contemporary practical speech recognition tasks. Even with the large corpora of manually transcribed speech data available…

cs.CL20203 cited

A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency

Tara N. Sainath, Yanzhang He, Bo Li +26

Thus far, end-to-end (E2E) models have not been shown to outperform state-of-the-art conventional models with respect to both quality, i.e., word error rate (WER), and latency, i.e…

eess.AS2020

Language-agnostic Multilingual Modeling

Arindrima Datta, Bhuvana Ramabhadran, Jesse Emond +2

Multilingual Automated Speech Recognition (ASR) systems allow for the joint training of data-rich and data-scarce languages in a single model. This enables data and parameter shari…

eess.AS201913 cited

A comparison of end-to-end models for long-form speech recognition

Chung-Cheng Chiu, Wei Han, Yu Zhang +11

End-to-end automatic speech recognition (ASR) models, including both attention-based models and the recurrent neural network transducer (RNN-T), have shown superior performance com…

eess.AS2019

Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model

Anjuli Kannan, Arindrima Datta, Tara N. Sainath +6

Multilingual end-to-end (E2E) models have shown great promise in expansion of automatic speech recognition (ASR) coverage of the world's languages. They have shown improvement over…

cs.CL20199 cited

Extracting Symptoms and their Status from Clinical Conversations

Nan Du, Kai Chen, Anjuli Kannan +3

This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status. Lack of any publicly…