[PDF][PDF] Recent advances in end-to-end automatic speech recognition
J Li - APSIPA Transactions on Signal and Information …, 2022 - nowpublishers.com
Recently, the speech community is seeing a significant trend of moving from deep neural
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …
An overview of end-to-end automatic speech recognition
D Wang, X Wang, S Lv - Symmetry, 2019 - mdpi.com
Automatic speech recognition, especially large vocabulary continuous speech recognition,
is an important issue in the field of machine learning. For a long time, the hidden Markov …
is an important issue in the field of machine learning. For a long time, the hidden Markov …
Speech-transformer: a no-recurrence sequence-to-sequence model for speech recognition
L Dong, S Xu, B Xu - 2018 IEEE international conference on …, 2018 - ieeexplore.ieee.org
Recurrent sequence-to-sequence models using encoder-decoder architecture have made
great progress in speech recognition task. However, they suffer from the drawback of slow …
great progress in speech recognition task. However, they suffer from the drawback of slow …
Deep learning scaling is predictable, empirically
J Hestness, S Narang, N Ardalani, G Diamos… - ar** real-time streaming transformer transducer for speech recognition on large-scale dataset
Recently, Transformer based end-to-end models have achieved great success in many
areas including speech recognition. However, compared to LSTM models, the heavy …
areas including speech recognition. However, compared to LSTM models, the heavy …
Deep learning enabled semantic communications with speech recognition and synthesis
In this paper, we develop a deep learning based semantic communication system for
speech transmission, named DeepSC-ST. We take the speech recognition and speech …
speech transmission, named DeepSC-ST. We take the speech recognition and speech …
The architectural implications of facebook's dnn-based personalized recommendation
The widespread application of deep learning has changed the landscape of computation in
data centers. In particular, personalized recommendation for content ranking is now largely …
data centers. In particular, personalized recommendation for content ranking is now largely …
[PDF][PDF] Deep Speech: Scaling up end-to-end speech recognition
A Hannun - arxiv preprint arxiv:1412.5567, 2014 - research.baidu.com
We present a state-of-the-art speech recognition system developed using end-to-end deep
learning. Our architecture is significantly simpler than traditional speech systems, which rely …
learning. Our architecture is significantly simpler than traditional speech systems, which rely …
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention--w/o Data Augmentation
We present state-of-the-art automatic speech recognition (ASR) systems employing a
standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder …
standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder …
Jasper: An end-to-end convolutional neural acoustic model
In this paper, we report state-of-the-art results on LibriSpeech among end-to-end speech
recognition models without any external training data. Our model, Jasper, uses only 1D …
recognition models without any external training data. Our model, Jasper, uses only 1D …