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End-To-End Speech Recognition

15 papers with code · Speech

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Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

8 Dec 2015tensorflow/models

We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages.

 SOTA for Speech Recognition on WSJ eval93 (using extra training data)

ACCENTED SPEECH RECOGNITION END-TO-END SPEECH RECOGNITION NOISY SPEECH RECOGNITION

Deep Speech: Scaling up end-to-end speech recognition

17 Dec 2014mozilla/DeepSpeech

We present a state-of-the-art speech recognition system developed using end-to-end deep learning.

ACCENTED SPEECH RECOGNITION END-TO-END SPEECH RECOGNITION

End-to-end speech recognition using lattice-free MMI

Interspeech 2018 2018 kaldi-asr/kaldi

We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models.

END-TO-END SPEECH RECOGNITION SPEECH RECOGNITION

Jasper: An End-to-End Convolutional Neural Acoustic Model

5 Apr 2019NVIDIA/OpenSeq2Seq

In this paper, we report state-of-the-art results on LibriSpeech among end-to-end speech recognition models without any external training data.

END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION

EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding

29 Jul 2015srvk/eesen

The performance of automatic speech recognition (ASR) has improved tremendously due to the application of deep neural networks (DNNs).

END-TO-END SPEECH RECOGNITION SPEECH RECOGNITION

RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation

8 May 2019rwth-i6/returnn

To the best knowledge of the authors, the results obtained when training on the full LibriSpeech training set, are the best published currently, both for the hybrid DNN/HMM and the attention-based systems.

END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION

Improved training of end-to-end attention models for speech recognition

8 May 2018rwth-i6/returnn

Sequence-to-sequence attention-based models on subword units allow simple open-vocabulary end-to-end speech recognition.

END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

18 Apr 2019shelling203/SpecAugment

On LibriSpeech, we achieve 6. 8% WER on test-other without the use of a language model, and 5. 8% WER with shallow fusion with a language model.

 SOTA for Speech Recognition on LibriSpeech test-clean (using extra training data)

DATA AUGMENTATION END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION

End-To-End Speech Recognition Using A High Rank LSTM-CTC Based Model

12 Mar 2019mobvoi/lstm_ctc

In this paper, we propose to use a high rank projection layer to replace the projection matrix.

DATA AUGMENTATION END-TO-END SPEECH RECOGNITION SPEECH RECOGNITION

Very Deep Self-Attention Networks for End-to-End Speech Recognition

30 Apr 2019quanpn90/NMTGMinor

Recently, end-to-end sequence-to-sequence models for speech recognition have gained significant interest in the research community.

END-TO-END SPEECH RECOGNITION SPEECH RECOGNITION