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01/24/2022
Endpoint Detection for Streaming End-to-End Multi-talker ASR
Streaming end-to-end multi-talker speech recognition aims at transcribin...
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09/17/2021
Continuous Streaming Multi-Talker ASR with Dual-path Transducers
Streaming recognition of multi-talker conversations has so far been eval...
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06/04/2021
Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition
Integrating external language models (LMs) into end-to-end (E2E) models ...
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04/05/2021
Streaming Multi-talker Speech Recognition with Joint Speaker Identification
In multi-talker scenarios such as meetings and conversations, speech pro...
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02/02/2021
Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition
The efficacy of external language model (LM) integration with existing e...
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11/26/2020
Streaming end-to-end multi-talker speech recognition
End-to-end multi-talker speech recognition is an emerging research trend...
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11/03/2020
Minimum Bayes Risk Training for End-to-End Speaker-Attributed ASR
Recently, an end-to-end speaker-attributed automatic speech recognition ...
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11/03/2020
Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition
The external language models (LM) integration remains a challenging task...
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10/23/2020
On Minimum Word Error Rate Training of the Hybrid Autoregressive Transducer
Hybrid Autoregressive Transducer (HAT) is a recently proposed end-to-end...
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05/19/2020
Exploring Transformers for Large-Scale Speech Recognition
While recurrent neural networks still largely define state-of-the-art sp...
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05/01/2020
Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition
Recently, the recurrent neural network transducer (RNN-T) architecture h...
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04/10/2020
Minimum Latency Training Strategies for Streaming Sequence-to-Sequence ASR
Recently, a few novel streaming attention-based sequence-to-sequence (S2...
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01/30/2020
Continuous speech separation: dataset and analysis
This paper describes a dataset and protocols for evaluating continuous s...
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12/06/2019
Semantic Mask for Transformer based End-to-End Speech Recognition
Attention-based encoder-decoder model has achieved impressive results fo...
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10/23/2019
A Transformer with Interleaved Self-attention and Convolution for Hybrid Acoustic Models
Transformer with self-attention has achieved great success in the area o...
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09/09/2019
Self-Teaching Networks
We propose self-teaching networks to improve the generalization capacity...
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07/12/2019
Pykaldi2: Yet another speech toolkit based on Kaldi and Pytorch
We introduce PyKaldi2 speech recognition toolkit implemented based on Ka...
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10/28/2017
A Study of All-Convolutional Encoders for Connectionist Temporal Classification
Connectionist temporal classification (CTC) is a popular sequence predic...
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08/01/2017
End-to-End Neural Segmental Models for Speech Recognition
Segmental models are an alternative to frame-based models for sequence p...
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06/28/2017
Toward Computation and Memory Efficient Neural Network Acoustic Models with Binary Weights and Activations
Neural network acoustic models have significantly advanced state of the ...
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04/05/2017
Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition
End-to-end training of deep learning-based models allows for implicit le...
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02/21/2017
Multitask Learning with CTC and Segmental CRF for Speech Recognition
Segmental conditional random fields (SCRFs) and connectionist temporal c...
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10/18/2016
Small-footprint Highway Deep Neural Networks for Speech Recognition
State-of-the-art speech recognition systems typically employ neural netw...
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09/26/2016
Multiplicative LSTM for sequence modelling
We introduce multiplicative LSTM (mLSTM), a recurrent neural network arc...
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08/02/2016
Knowledge Distillation for Small-footprint Highway Networks
Deep learning has significantly advanced state-of-the-art of speech reco...
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07/07/2016
Sequence Training and Adaptation of Highway Deep Neural Networks
Highway deep neural network (HDNN) is a type of depth-gated feedforward ...
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03/01/2016
Segmental Recurrent Neural Networks for End-to-end Speech Recognition
We study the segmental recurrent neural network for end-to-end acoustic ...
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12/14/2015
Small-footprint Deep Neural Networks with Highway Connections for Speech Recognition
For speech recognition, deep neural networks (DNNs) have significantly i...
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10/31/2015
Top-down Tree Long Short-Term Memory Networks
Long Short-Term Memory (LSTM) networks, a type of recurrent neural netwo...
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11/04/2014
