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 24012450 of 6433 papers

TitleStatusHype
Samrómur Children: An Icelandic Speech Corpus0
Towards an Open-Source Dutch Speech Recognition System for the Healthcare Domain0
Extracting Linguistic Knowledge from Speech: A Study of Stop Realization in 5 Romance Languages0
Samrómur: Crowd-sourcing large amounts of data0
Mesures linguistiques automatiques pour l’évaluation des systèmes de Reconnaissance Automatique de la Parole (Automated linguistic measures for automatic speech recognition systems’ evaluation)0
Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages0
Adversarial synthesis based data-augmentation for code-switched spoken language identification0
Speaker Identification using Speech Recognition0
Adaptive Activation Network For Low Resource Multilingual Speech Recognition0
Is Lip Region-of-Interest Sufficient for Lipreading?0
Punctuation Restoration in Spanish Customer Support Transcripts using Transfer Learning0
Contrastive Siamese Network for Semi-supervised Speech Recognition0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning0
Global Normalization for Streaming Speech Recognition in a Modular FrameworkCode1
Contextual Adapters for Personalized Speech Recognition in Neural Transducers0
Clinical Dialogue Transcription Error Correction using Seq2Seq Models0
Joint Training of Speech Enhancement and Self-supervised Model for Noise-robust ASR0
FLEURS: Few-shot Learning Evaluation of Universal Representations of SpeechCode0
On Building Spoken Language Understanding Systems for Low Resourced Languages0
Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentation0
Improving CTC-based ASR Models with Gated Interlayer Collaboration0
Heterogeneous Reservoir Computing Models for Persian Speech Recognition0
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech0
Semantic-preserved Communication System for Highly Efficient Speech Transmission0
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling0
Adaptive multilingual speech recognition with pretrained models0
Multi-Level Modeling Units for End-to-End Mandarin Speech Recognition0
Training Efficient CNNS: Tweaking the Nuts and Bolts of Neural Networks for Lighter, Faster and Robust ModelsCode0
Calibrate and Refine! A Novel and Agile Framework for ASR-error Robust Intent Detection0
Deep Learning for Visual Speech Analysis: A Survey0
Language Models with Image Descriptors are Strong Few-Shot Video-Language LearnersCode1
Self-Supervised Speech Representation Learning: A Review0
NeuralEcho: A Self-Attentive Recurrent Neural Network For Unified Acoustic Echo Suppression And Speech Enhancement0
PaddleSpeech: An Easy-to-Use All-in-One Speech ToolkitCode6
Predicting electrode array impedance after one month from cochlear implantation surgery0
Set-based Meta-Interpolation for Few-Task Meta-Learning0
Content-Context Factorized Representations for Automated Speech Recognition0
Automatic Spoken Language Identification using a Time-Delay Neural Network0
Insights on Neural Representations for End-to-End Speech Recognition0
Minimising Biasing Word Errors for Contextual ASR with the Tree-Constrained Pointer Generator0
Streaming Noise Context Aware Enhancement For Automatic Speech Recognition in Multi-Talker Environments0
Deploying self-supervised learning in the wild for hybrid automatic speech recognition0
Accented Speech Recognition: Benchmarking, Pre-training, and Diverse Data0
Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challenge0
Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing0
Who Are We Talking About? Handling Person Names in Speech Translation0
Unified Modeling of Multi-Domain Multi-Device ASR Systems0
Personalized Adversarial Data Augmentation for Dysarthric and Elderly Speech Recognition0
Improved Meta Learning for Low Resource Speech Recognition0
A Closer Look at Audio-Visual Multi-Person Speech Recognition and Active Speaker Selection0
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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