Connectionist Temporal Classification (CTC) models are popular for their...
Speech representations learned in a self-supervised fashion from massive...
Conformer-based end-to-end models have become ubiquitous these days and ...
Masked Language Models (MLMs) have proven to be effective for second-pas...
End-to-end ASR models trained on large amount of data tend to be implici...
Recently, there has been an increasing interest in unifying streaming an...
Language models have been shown to perform better with an increase in sc...
In this work, we define barge-in verification as a supervised learning t...
End-to-end speech recognition models trained using joint Connectionist
T...
Automatic Speech Recognition (ASR) systems have found their use in numer...
Automatic Speech Recognition (ASR) systems have found their use in numer...
Accurate recognition of slot values such as domain specific words or nam...
Automatic Speech Recognition (ASR) robustness toward slot entities are
c...
Neural Language Models (NLM), when trained and evaluated with context
sp...
Goal-oriented conversational interfaces are designed to accomplish speci...
While there have been several contributions exploring state of the art
t...
Much recent work on Spoken Language Understanding (SLU) falls short in a...
In this work, we explore a multimodal semi-supervised learning approach ...
Automatic speech recognition (ASR) systems in the medical domain that fo...
Automatic speech recognition (ASR) systems in the medical domain that fo...
Simulation-to-simulation and simulation-to-real world transfer of neural...
Chronic disease progression is emerging as an important area of investme...
Robustness to capitalization errors is a highly desirable characteristic...