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 251300 of 6433 papers

TitleStatusHype
IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languagesCode1
Integrating Lattice-Free MMI into End-to-End Speech RecognitionCode1
Investigating the Reordering Capability in CTC-based Non-Autoregressive End-to-End Speech TranslationCode1
Investigation of End-To-End Speaker-Attributed ASR for Continuous Multi-Talker RecordingsCode1
DENT-DDSP: Data-efficient noisy speech generator using differentiable digital signal processors for explicit distortion modelling and noise-robust speech recognitionCode1
DiaCorrect: Error Correction Back-end For Speaker DiarizationCode1
Deep Speech 2: End-to-End Speech Recognition in English and MandarinCode1
Deep Sparse Conformer for Speech RecognitionCode1
Deep Speech: Scaling up end-to-end speech recognitionCode1
Deep Contextualized Acoustic Representations For Semi-Supervised Speech RecognitionCode1
Deep Compressive Offloading: Speeding Up Neural Network Inference by Trading Edge Computation for Network LatencyCode1
Deep Learning Enabled Semantic Communications with Speech Recognition and SynthesisCode1
Deep transfer operator learning for partial differential equations under conditional shiftCode1
Do VSR Models Generalize Beyond LRS3?Code1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aidsCode1
D4AM: A General Denoising Framework for Downstream Acoustic ModelsCode1
Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across ModalitiesCode1
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech RecognitionCode1
Cross-Speaker Encoding Network for Multi-Talker Speech RecognitionCode1
Cross-Modal Global Interaction and Local Alignment for Audio-Visual Speech RecognitionCode1
3M: Multi-loss, Multi-path and Multi-level Neural Networks for speech recognitionCode1
Cross Attention Augmented Transducer Networks for Simultaneous TranslationCode1
CTC-synchronous Training for Monotonic Attention ModelCode1
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector QuantizationCode1
CopyNE: Better Contextual ASR by Copying Named EntitiesCode1
Convolutional Neural Network (CNN) to reduce construction loss in JPEG compression caused by Discrete Fourier Transform (DFT)Code1
CORAA: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian PortugueseCode1
CoVoST 2 and Massively Multilingual Speech-to-Text TranslationCode1
Continuous speech separation: dataset and analysisCode1
Accented Speech Recognition With Accent-specific CodebooksCode1
Contrastive Learning-Based Audio to Lyrics Alignment for Multiple LanguagesCode1
BERTphone: Phonetically-Aware Encoder Representations for Utterance-Level Speaker and Language RecognitionCode1
Continual Test-time Adaptation for End-to-end Speech Recognition on Noisy SpeechCode1
Controlling Whisper: Universal Acoustic Adversarial Attacks to Control Speech Foundation ModelsCode1
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN ExecutionCode1
Deep Audio-Visual Speech RecognitionCode1
Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech TranslationCode1
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech RecognitionCode1
Goodness of Pronunciation Pipelines for OOV ProblemCode1
Computer-Generated Music for Tabletop Role-Playing GamesCode1
Comparative layer-wise analysis of self-supervised speech modelsCode1
Communication-Efficient Learning of Deep Networks from Decentralized DataCode1
Compiling ONNX Neural Network Models Using MLIRCode1
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech RecognitionCode1
CMULAB: An Open-Source Framework for Training and Deployment of Natural Language Processing ModelsCode1
Combining Frame-Synchronous and Label-Synchronous Systems for Speech RecognitionCode1
CLSRIL-23: Cross Lingual Speech Representations for Indic LanguagesCode1
Common Voice: A Massively-Multilingual Speech CorpusCode1
CIF: Continuous Integrate-and-Fire for End-to-End Speech RecognitionCode1
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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