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01/28/2022
Improving End-to-End Models for Set Prediction in Spoken Language Understanding
The goal of spoken language understanding (SLU) systems is to determine ...
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08/27/2021
4-bit Quantization of LSTM-based Speech Recognition Models
We investigate the impact of aggressive low-precision representations of...
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08/24/2021
Reducing Exposure Bias in Training Recurrent Neural Network Transducers
When recurrent neural network transducers (RNNTs) are trained using the ...
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08/18/2021
Integrating Dialog History into End-to-End Spoken Language Understanding Systems
End-to-end spoken language understanding (SLU) systems that process huma...
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05/03/2021
On the limit of English conversational speech recognition
In our previous work we demonstrated that a single headed attention enco...
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04/08/2021
RNN Transducer Models For Spoken Language Understanding
We present a comprehensive study on building and adapting RNN transducer...
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11/16/2020
End-to-end spoken language understanding using transformer networks and self-supervised pre-trained features
Transformer networks and self-supervised pre-training have consistently ...
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09/30/2020
End-to-End Spoken Language Understanding Without Full Transcripts
An essential component of spoken language understanding (SLU) is slot fi...
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01/20/2020
Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard-300
It is generally believed that direct sequence-to-sequence (seq2seq) spee...
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08/09/2019
Challenging the Boundaries of Speech Recognition: The MALACH Corpus
There has been huge progress in speech recognition over the last several...
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04/30/2019
English Broadcast News Speech Recognition by Humans and Machines
With recent advances in deep learning, considerable attention has been g...
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10/16/2018
