164 citations · 535 across the 44 of their papers we have counts for
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Building competitive direct acoustics-to-word models for English conversational speech recognition
Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran +2
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have received increasing attention compared to conventional sub-word based automatic speech recognition models usin…
Language Modeling with Highway LSTM
Gakuto Kurata, Bhuvana Ramabhadran, George Saon +1
Language models (LMs) based on Long Short Term Memory (LSTM) have shown good gains in many automatic speech recognition tasks. In this paper, we extend an LSTM by adding highway ne…
Direct Acoustics-to-Word Models for English Conversational Speech Recognition
Kartik Audhkhasi, Bhuvana Ramabhadran, George Saon +2
Recent work on end-to-end automatic speech recognition (ASR) has shown that the connectionist temporal classification (CTC) loss can be used to convert acoustics to phone or charac…
English Conversational Telephone Speech Recognition by Humans and Machines
George Saon, Gakuto Kurata, Tom Sercu +9
One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major sp…
End-to-End ASR-free Keyword Search from Speech
Kartik Audhkhasi, Andrew Rosenberg, Abhinav Sethy +2
End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) sy…