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 20012050 of 6433 papers

TitleStatusHype
Improving Children's Speech Recognition by Fine-tuning Self-supervised Adult Speech RepresentationsCode0
Towards A Unified Conformer Structure: from ASR to ASV TaskCode2
MT4SSL: Boosting Self-Supervised Speech Representation Learning by Integrating Multiple TargetsCode1
FullPack: Full Vector Utilization for Sub-Byte Quantized Inference on General Purpose CPUs0
Handling Trade-Offs in Speech Separation with Sparsely-Gated Mixture of Experts0
An Adapter based Multi-label Pre-training for Speech Separation and Enhancement0
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation0
Continuous Soft Pseudo-Labeling in ASR0
The Far Side of Failure: Investigating the Impact of Speech Recognition Errors on Subsequent Dementia ClassificationCode0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding0
Self-supervised learning with bi-label masked speech prediction for streaming multi-talker speech recognition0
Adaptive Multi-Corpora Language Model Training for Speech Recognition0
Improving Noisy Student Training on Non-target Domain Data for Automatic Speech Recognition0
Speech Emotion Recognition Based on Self-Attention Weight Correction for Acoustic and Text Features0
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR ErrorsCode0
ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control CommunicationsCode1
Comparative layer-wise analysis of self-supervised speech modelsCode1
Towards Improved Room Impulse Response Estimation for Speech RecognitionCode1
End-to-End Evaluation of a Spoken Dialogue System for Learning Basic Mathematics0
Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition0
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR0
LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers0
Evaluation of Automated Speech Recognition Systems for Conversational Speech: A Linguistic Perspective0
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech0
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion0
Minimum Latency Training of Sequence Transducers for Streaming End-to-End Speech Recognition0
Multi-blank Transducers for Speech RecognitionCode1
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability0
Biased Self-supervised learning for ASR0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks0
Leveraging Domain Features for Detecting Adversarial Attacks Against Deep Speech Recognition in Noise0
Streaming Audio-Visual Speech Recognition with Alignment Regularization0
Probing Statistical Representations For End-To-End ASR0
Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition0
Phonetic-assisted Multi-Target Units Modeling for Improving Conformer-Transducer ASR system0
BECTRA: Transducer-based End-to-End ASR with BERT-Enhanced Encoder0
Towards Zero-Shot Code-Switched Speech Recognition0
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech ProcessingCode1
InterMPL: Momentum Pseudo-Labeling with Intermediate CTC Loss0
More Speaking or More Speakers?0
Variable Attention Masking for Configurable Transformer Transducer Speech Recognition0
Monolingual Recognizers Fusion for Code-switching Speech Recognition0
Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loop0
Mandarin-English Code-Switching Speech Recognition System for Specific Domain0
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students0
Avoid Overthinking in Self-Supervised Models for Speech Recognition0
Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems0
Adapting self-supervised models to multi-talker speech recognition using speaker embeddings0
A Comparative Study on Multichannel Speaker-Attributed Automatic Speech Recognition in Multi-party Meetings0
Speech-text based multi-modal training with bidirectional attention for improved speech recognitionCode0
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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