184 citations · 229 across the 10 of their papers we have counts for
4 papers · 1 filter
Streaming End-to-end Speech Recognition For Mobile Devices
Yanzhang He, Tara N. Sainath, Rohit Prabhavalkar +17
End-to-end (E2E) models, which directly predict output character sequences given input speech, are good candidates for on-device speech recognition. E2E models, however, present nu…
Contextual Speech Recognition with Difficult Negative Training Examples
Uri Alon, Golan Pundak, Tara N. Sainath
Improving the representation of contextual information is key to unlocking the potential of end-to-end (E2E) automatic speech recognition (ASR). In this work, we present a novel an…
Toward domain-invariant speech recognition via large scale training
Arun Narayanan, Ananya Misra, Khe Chai Sim +6
Current state-of-the-art automatic speech recognition systems are trained to work in specific `domains', defined based on factors like application, sampling rate and codec. When su…
Deep context: end-to-end contextual speech recognition
Golan Pundak, Tara N. Sainath, Rohit Prabhavalkar +2
In automatic speech recognition (ASR) what a user says depends on the particular context she is in. Typically, this context is represented as a set of word n-grams. In this work, w…