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Speech Recognition

326 papers with code · Robots

Speech recognition is the task of recognising speech within audio and converting it into text.

( Image credit: SpecAugment )

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Greatest papers with code

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.

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

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

17 Dec 2014mozilla/STT

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

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

18 Apr 2019mozilla/DeepSpeech

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.

Ranked #2 on Speech Recognition on Hub5'00 SwitchBoard (SwitchBoard metric)

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

wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

NeurIPS 2020 pytorch/fairseq

We show for the first time that learning powerful representations from speech audio alone followed by fine-tuning on transcribed speech can outperform the best semi-supervised methods while being conceptually simpler.

 Ranked #1 on Speech Recognition on TIMIT (using extra training data)

QUANTIZATION SELF-SUPERVISED LEARNING SPEECH RECOGNITION

vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations

ICLR 2020 pytorch/fairseq

We propose vq-wav2vec to learn discrete representations of audio segments through a wav2vec-style self-supervised context prediction task.

Ranked #2 on Speech Recognition on TIMIT (using extra training data)

SELF-SUPERVISED LEARNING SPEECH RECOGNITION

wav2vec: Unsupervised Pre-training for Speech Recognition

11 Apr 2019pytorch/fairseq

Our experiments on WSJ reduce WER of a strong character-based log-mel filterbank baseline by up to 36% when only a few hours of transcribed data is available.

Ranked #5 on Speech Recognition on TIMIT (using extra training data)

SPEECH RECOGNITION UNSUPERVISED PRE-TRAINING

fairseq S2T: Fast Speech-to-Text Modeling with fairseq

11 Oct 2020pytorch/fairseq

We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) modeling tasks such as end-to-end speech recognition and speech-to-text translation.

END-TO-END SPEECH RECOGNITION MACHINE TRANSLATION MULTI-TASK LEARNING SPEECH RECOGNITION

Semi-Supervised Speech Recognition via Local Prior Matching

24 Feb 2020facebookresearch/wav2letter

For sequence transduction tasks like speech recognition, a strong structured prior model encodes rich information about the target space, implicitly ruling out invalid sequences by assigning them low probability.

LANGUAGE MODELLING SPEECH RECOGNITION

wav2letter++: The Fastest Open-source Speech Recognition System

18 Dec 2018facebookresearch/wav2letter

This paper introduces wav2letter++, the fastest open-source deep learning speech recognition framework.

SPEECH RECOGNITION

End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures

19 Nov 2019facebookresearch/wav2letter

We study pseudo-labeling for the semi-supervised training of ResNet, Time-Depth Separable ConvNets, and Transformers for speech recognition, with either CTC or Seq2Seq loss functions.

END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION