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09/19/2023
Semi-Autoregressive Streaming ASR With Label Context
Non-autoregressive (NAR) modeling has gained significant interest in spe...
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09/07/2023
Multiple Representation Transfer from Large Language Models to End-to-End ASR Systems
Transferring the knowledge of large language models (LLMs) is a promisin...
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02/27/2023
Diagonal State Space Augmented Transformers for Speech Recognition
We improve on the popular conformer architecture by replacing the depthw...
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08/03/2022
VQ-T: RNN Transducers using Vector-Quantized Prediction Network States
Beam search, which is the dominant ASR decoding algorithm for end-to-end...
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07/28/2022
Extending RNN-T-based speech recognition systems with emotion and language classification
Speech transcription, emotion recognition, and language identification a...
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06/16/2022
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization
We report on aggressive quantization strategies that greatly accelerate ...
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04/01/2022
Effect and Analysis of Large-scale Language Model Rescoring on Competitive ASR Systems
Large-scale language models (LLMs) such as GPT-2, BERT and RoBERTa have ...
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03/29/2022
Improving Generalization of Deep Neural Network Acoustic Models with Length Perturbation and N-best Based Label Smoothing
We introduce two techniques, length perturbation and n-best based label ...
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02/26/2022
Towards Reducing the Need for Speech Training Data To Build Spoken Language Understanding Systems
The lack of speech data annotated with labels required for spoken langua...
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02/26/2022
Integrating Text Inputs For Training and Adapting RNN Transducer ASR Models
Compared to hybrid automatic speech recognition (ASR) systems that use a...
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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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10/21/2021
Asynchronous Decentralized Distributed Training of Acoustic Models
Large-scale distributed training of deep acoustic models plays an import...
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10/04/2021
Towards efficient end-to-end speech recognition with biologically-inspired neural networks
Automatic speech recognition (ASR) is a capability which enables a progr...
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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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03/17/2021
Advancing RNN Transducer Technology for Speech Recognition
We investigate a set of techniques for RNN Transducers (RNN-Ts) that wer...
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02/24/2020
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition
The past decade has witnessed great progress in Automatic Speech Recogni...
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02/04/2020
Improving Efficiency in Large-Scale Decentralized Distributed Training
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
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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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07/10/2019
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Modern Automatic Speech Recognition (ASR) systems rely on distributed de...
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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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04/10/2019
Distributed Deep Learning Strategies For Automatic Speech Recognition
In this paper, we propose and investigate a variety of distributed deep ...
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12/08/2017
Building competitive direct acoustics-to-word models for English conversational speech recognition
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have re...
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10/17/2017
Embedding-Based Speaker Adaptive Training of Deep Neural Networks
An embedding-based speaker adaptive training (SAT) approach is proposed ...
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09/19/2017
Language Modeling with Highway LSTM
Language models (LMs) based on Long Short Term Memory (LSTM) have shown ...
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03/22/2017
Direct Acoustics-to-Word Models for English Conversational Speech Recognition
Recent work on end-to-end automatic speech recognition (ASR) has shown t...
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03/06/2017
English Conversational Telephone Speech Recognition by Humans and Machines
One of the most difficult speech recognition tasks is accurate recogniti...
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04/27/2016
The IBM 2016 English Conversational Telephone Speech Recognition System
We describe a collection of acoustic and language modeling techniques th...
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09/05/2013