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Large Vocabulary Continuous Speech Recognition

11 papers with code · Speech

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Purely sequence-trained neural networks for ASR based on lattice-free MMI

INTERSPEECH 2016 2016 kaldi-asr/kaldi

Models trained with LFMMI provide a relative word error rate reduction of ∼11. 5%, over those trained with cross-entropy objective function, and ∼8%, over those trained with cross-entropy and sMBR objective functions.

LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs

12 Aug 2014baidu-research/warp-ctc

This approach to decoding enables first-pass speech recognition with a language model, completely unaided by the cumbersome infrastructure of HMM-based systems.

LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

End-to-End Attention-based Large Vocabulary Speech Recognition

18 Aug 2015rizar/attention-lvcsr

Many of the current state-of-the-art Large Vocabulary Continuous Speech Recognition Systems (LVCSR) are hybrids of neural networks and Hidden Markov Models (HMMs).

ACOUSTIC MODELLING LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition

5 Sep 2018georgesterpu/Sigmedia-AVSR

Automatic speech recognition can potentially benefit from the lip motion patterns, complementing acoustic speech to improve the overall recognition performance, particularly in noise.

LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

Deep-FSMN for Large Vocabulary Continuous Speech Recognition

4 Mar 2018yangxueruivs/DFSMN

In a 20000 hours Mandarin recognition task, the LFR trained DFSMN can achieve more than 20% relative improvement compared to the LFR trained BLSTM.

LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

Trace norm regularization and faster inference for embedded speech recognition RNNs

ICLR 2018 paddlepaddle/farm

We propose and evaluate new techniques for compressing and speeding up dense matrix multiplications as found in the fully connected and recurrent layers of neural networks for embedded large vocabulary continuous speech recognition (LVCSR).

LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

A Survey of Recent DNN Architectures on the TIMIT Phone Recognition Task

19 Jun 2018OrcusCZ/NNAcousticModeling

In this survey paper, we have evaluated several recent deep neural network (DNN) architectures on a TIMIT phone recognition task.

LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

Recurrent DNNs and its Ensembles on the TIMIT Phone Recognition Task

19 Jun 2018OrcusCZ/NNAcousticModeling

Also, we prefer the phone recognition task because it is much more sensitive to an acoustic model quality than a large vocabulary continuous speech recognition task.

LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION

A segmental framework for fully-unsupervised large-vocabulary speech recognition

22 Jun 2016kamperh/recipe_bucktsong_awe

We also show that the discovered clusters can be made less speaker- and gender-specific by using an unsupervised autoencoder-like feature extractor to learn better frame-level features (prior to embedding).

LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION