SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 42514300 of 6433 papers

TitleStatusHype
power-law nonlinearity with maximally uniform distribution criterion for improved neural network training in automatic speech recognition0
Harnessing Evolution of Multi-Turn Conversations for Effective Answer RetrievalCode0
Role of non-linear data processing on speech recognition task in the framework of reservoir computing0
Statistical Testing on ASR Performance via Blockwise Bootstrap0
Generating Synthetic Audio Data for Attention-Based Speech Recognition Systems0
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesCode0
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications0
End-to-end training of time domain audio separation and recognition0
Detecting Adversarial Attacks On Audiovisual Speech Recognition0
Libri-Light: A Benchmark for ASR with Limited or No SupervisionCode1
Application of Word2vec in Phoneme RecognitionCode0
Continuous Speech Recognition using EEG and Video0
Synchronous Speech Recognition and Speech-to-Text Translation with Interactive DecodingCode0
Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entities0
Common Voice: A Massively-Multilingual Speech CorpusCode1
On Neural Phone Recognition of Mixed-Source ECoG Signals0
Leveraging End-to-End Speech Recognition with Neural Architecture Search0
SpecAugment on Large Scale Datasets0
A Novel Topology for End-to-end Temporal Classification and Segmentation with Recurrent Neural Network0
A Multi Purpose and Large Scale Speech Corpus in Persian and English for Speaker and Speech Recognition: the DeepMine Database0
Audio-attention discriminative language model for ASR rescoring0
Re-Translation Strategies For Long Form, Simultaneous, Spoken Language TranslationCode0
Visualizing Deep Neural Networks for Speech Recognition with Learned Topographic Filter Maps0
Synchronous Transformers for End-to-End Speech Recognition0
Semantic Mask for Transformer based End-to-End Speech RecognitionCode0
A Resource for Computational Experiments on MapudungunCode1
Integrating Knowledge into End-to-End Speech Recognition from External Text-Only Data0
Deep Contextualized Acoustic Representations For Semi-Supervised Speech RecognitionCode1
Language Model Bootstrapping Using Neural Machine Translation For Conversational Speech Recognition0
Biometrics Recognition Using Deep Learning: A SurveyCode0
Improving Voice Separation by Incorporating End-to-end Speech RecognitionCode0
Kurdish (Sorani) Speech to Text: Presenting an Experimental DatasetCode0
Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition0
Designing the Next Generation of Intelligent Personal Robotic Assistants for the Physically Impaired0
ASR is all you need: cross-modal distillation for lip reading0
Multimodal Machine Translation through Visuals and Speech0
AIPNet: Generative Adversarial Pre-training of Accent-invariant Networks for End-to-end Speech Recognition0
Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers0
ATCSpeech: a multilingual pilot-controller speech corpus from real Air Traffic Control environment0
Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction0
Independent language modeling architecture for end-to-end ASR0
Improving EEG based Continuous Speech Recognition0
Recurrent Neural Networks (RNNs): A gentle Introduction and Overview0
Improving N-gram Language Models with Pre-trained Deep Transformer0
Cantonese Automatic Speech Recognition Using Transfer Learning from Mandarin0
On using 2D sequence-to-sequence models for speech recognition0
CAT: CRF-based ASR ToolkitCode0
End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern ArchitecturesCode0
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech RecognitionCode0
Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified