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 201250 of 6433 papers

TitleStatusHype
Automatic Speech Recognition for Speech Assessment of Persian Preschool ChildrenCode1
Automatic Speech Recognition Benchmark for Air-Traffic CommunicationsCode1
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling InsightsCode1
Automatic speech recognition for the Nepali language using CNN, bidirectional LSTM and ResNetCode1
A Variance-Preserving Interpolation Approach for Diffusion Models with Applications to Single Channel Speech Enhancement and RecognitionCode1
Adaptation of Whisper models to child speech recognitionCode1
Framework for Curating Speech Datasets and Evaluating ASR Systems: A Case Study for PolishCode1
AV Taris: Online Audio-Visual Speech RecognitionCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
Back Translation for Speech-to-text Translation Without TranscriptsCode1
Adapting End-to-End Speech Recognition for Readable SubtitlesCode1
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural NetworksCode1
Distilling the Knowledge of BERT for Sequence-to-Sequence ASRCode1
DistilXLSR: A Light Weight Cross-Lingual Speech Representation ModelCode1
Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech EnhancementCode1
Emotion Recognition in Audio and Video Using Deep Neural NetworksCode1
BembaSpeech: A Speech Recognition Corpus for the Bemba LanguageCode1
EnCodecMAE: Leveraging neural codecs for universal audio representation learningCode1
Adapting Pretrained Transformer to Lattices for Spoken Language UnderstandingCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control CommunicationsCode1
End-to-End Single-Channel Speaker-Turn Aware Conversational Speech TranslationCode1
BIG-C: a Multimodal Multi-Purpose Dataset for BembaCode1
CI-AVSR: A Cantonese Audio-Visual Speech Datasetfor In-car Command RecognitionCode1
Espresso: A Fast End-to-end Neural Speech Recognition ToolkitCode1
Evaluating Speech Synthesis by Training Recognizers on Synthetic SpeechCode1
Attention-based Contextual Language Model Adaptation for Speech RecognitionCode1
ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of KaldiCode1
Attention-based Audio-Visual Fusion for Robust Automatic Speech RecognitionCode1
Factorized Neural Transducer for Efficient Language Model AdaptationCode1
Attention-Based Models for Speech RecognitionCode1
Attack on practical speaker verification system using universal adversarial perturbationsCode1
A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition BaselineCode1
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
Distilling a Pretrained Language Model to a Multilingual ASR ModelCode1
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksCode1
A Comparison of Methods for OOV-word Recognition on a New Public DatasetCode1
Bridging the Gaps of Both Modality and Language: Synchronous Bilingual CTC for Speech Translation and Speech RecognitionCode1
dMel: Speech Tokenization made SimpleCode1
Byakto Speech: Real-time long speech synthesis with convolutional neural network: Transfer learning from English to BanglaCode1
AdaScale SGD: A User-Friendly Algorithm for Distributed TrainingCode1
Calibrating Transformers via Sparse Gaussian ProcessesCode1
CAPE: Encoding Relative Positions with Continuous Augmented Positional EmbeddingsCode1
Can we use Common Voice to train a Multi-Speaker TTS system?Code1
A Cross-Modal Approach to Silent Speech with LLM-Enhanced RecognitionCode1
FlanEC: Exploring Flan-T5 for Post-ASR Error CorrectionCode1
Differentiable Weighted Finite-State TransducersCode1
ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control CommunicationsCode1
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
A transfer learning based approach for pronunciation scoringCode1
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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
9Gated ConvNetsWord Error Rate (WER)4.8Unverified
10HMM-TDNN + iVectorsWord 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
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
8DNN MPEPercentage error12.9Unverified
9DNN MMIPercentage error12.9Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage 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
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
7Convolutional Speech RecognitionWord 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