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 51015150 of 6433 papers

TitleStatusHype
Reexamining Racial Disparities in Automatic Speech Recognition Performance: The Role of Confounding by Provenance0
Refining Automatic Speech Recognition System for older adults0
Refining Self-Supervised Learnt Speech Representation using Brain Activations0
Regeneration Learning: A Learning Paradigm for Data Generation0
Regularized Forward-Backward Decoder for Attention Models0
Regularizing Contrastive Predictive Coding for Speech Applications0
Regularizing Learnable Feature Extraction for Automatic Speech Recognition0
Reinforcement Learning Based Speech Enhancement for Robust Speech Recognition0
Reinforcement Learning of Multi-Issue Negotiation Dialogue Policies0
Reinforcement Learning of Speech Recognition System Based on Policy Gradient and Hypothesis Selection0
Relative Positional Encoding for Speech Recognition and Direct Translation0
Relaxing the Conditional Independence Assumption of CTC-based ASR by Conditioning on Intermediate Predictions0
Remember the context! ASR slot error correction through memorization0
Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients0
Remote Speech Technology for Speech Professionals - the CloudCAST initiative0
Replacing Human Audio with Synthetic Audio for On-device Unspoken Punctuation Prediction0
Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition0
Representation Learning to Classify and Detect Adversarial Attacks against Speaker and Speech Recognition Systems0
Representation Learning With Hidden Unit Clustering For Low Resource Speech Applications0
RescoreBERT: Discriminative Speech Recognition Rescoring with BERT0
RescueSpeech: A German Corpus for Speech Recognition in Search and Rescue Domain0
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks0
Research Challenges in Building a Voice-based Artificial Personal Shopper - Position Paper0
Research on an improved Conformer end-to-end Speech Recognition Model with R-Drop Structure0
Research on Modeling Units of Transformer Transducer for Mandarin Speech Recognition0
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech0
Residual Convolutional CTC Networks for Automatic Speech Recognition0
Residual Energy-Based Models for End-to-End Speech Recognition0
Residual Language Model for End-to-end Speech Recognition0
ResidualTransformer: Residual Low-Rank Learning with Weight-Sharing for Transformer Layers0
Resilience of Large Language Models for Noisy Instructions0
Resolution limits on visual speech recognition0
Resolving Transcription Ambiguity in Spanish: A Hybrid Acoustic-Lexical System for Punctuation Restoration0
Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion0
Resource-Constrained Federated Learning with Heterogeneous Labels and Models0
Resource-Efficient Adaptation of Speech Foundation Models for Multi-Speaker ASR0
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion0
Resource Evaluation for Usable Speech Interfaces: Utilizing Human-Human Dialogue0
Response Generation Based on Hierarchical Semantic Structure with POMDP Re-ranking for Conversational Dialogue Systems0
Re-synchronization using the Hand Preceding Model for Multi-modal Fusion in Automatic Continuous Cued Speech Recognition0
Rethinking End-to-End Evaluation of Decomposable Tasks: A Case Study on Spoken Language Understanding0
Rethinking Full Connectivity in Recurrent Neural Networks0
Rethinking Mamba in Speech Processing by Self-Supervised Models0
Rethinking Processing Distortions: Disentangling the Impact of Speech Enhancement Errors on Speech Recognition Performance0
Rethinking Speech Recognition with A Multimodal Perspective via Acoustic and Semantic Cooperative Decoding0
Retraining-free Customized ASR for Enharmonic Words Based on a Named-Entity-Aware Model and Phoneme Similarity Estimation0
Retrieval Augmented Correction of Named Entity Speech Recognition Errors0
Retrieval-Augmented Speech Recognition Approach for Domain Challenges0
Retrieval-Enhanced Few-Shot Prompting for Speech Event Extraction0
Retrieval Term Prediction Using Deep Belief Networks0
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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