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 21012150 of 6433 papers

TitleStatusHype
Does Joint Training Really Help Cascaded Speech Translation?Code0
Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimationCode1
ESB: A Benchmark For Multi-Domain End-to-End Speech RecognitionCode1
Investigating self-supervised, weakly supervised and fully supervised training approaches for multi-domain automatic speech recognition: a study on Bangladeshi Bangla0
Guided contrastive self-supervised pre-training for automatic speech recognition0
Can Visual Context Improve Automatic Speech Recognition for an Embodied Agent?0
Optimizing Bilingual Neural Transducer with Synthetic Code-switching Text Generation0
Deep LSTM Spoken Term Detection using Wav2Vec 2.0 Recognizer0
Anchored Speech Recognition with Neural Transducers0
Improving Semi-supervised End-to-end Automatic Speech Recognition using CycleGAN and Inter-domain Losses0
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR0
Tourist Guidance Robot Based on HyperCLOVA0
Speaker- and Age-Invariant Training for Child Acoustic Modeling Using Adversarial Multi-Task Learning0
Simple and Effective Unsupervised Speech Translation0
Generalizing in the Real World with Representation LearningCode1
Discrete Cross-Modal Alignment Enables Zero-Shot Speech TranslationCode0
Towards Personalization of CTC Speech Recognition Models with Contextual Adapters and Adaptive Boosting0
Maestro-U: Leveraging joint speech-text representation learning for zero supervised speech ASR0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability0
Sub-8-bit quantization for on-device speech recognition: a regularization-free approach0
Towards Relation Extraction From SpeechCode1
Language-agnostic Code-Switching in Sequence-To-Sequence Speech Recognition0
Continuous Pseudo-Labeling from the Start0
A Treatise On FST Lattice Based MMI Training0
Acoustic-aware Non-autoregressive Spell Correction with Mask Sample Decoding0
Learning Invariant Representation and Risk Minimized for Unsupervised Accent Domain Adaptation0
Learning to Jointly Transcribe and Subtitle for End-to-End Spontaneous Speech Recognition0
LeVoice ASR Systems for the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge0
Bringing NURC/SP to Digital Life: the Role of Open-source Automatic Speech Recognition ModelsCode0
TransFusion: Transcribing Speech with Multinomial DiffusionCode1
Experiments on Turkish ASR with Self-Supervised Speech Representation Learning0
Multilingual Zero Resource Speech Recognition Base on Self-Supervise Pre-Trained Acoustic Models0
Can we use Common Voice to train a Multi-Speaker TTS system?Code1
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition0
Foundation TransformersCode1
Summary on the ISCSLP 2022 Chinese-English Code-Switching ASR Challenge0
A context-aware knowledge transferring strategy for CTC-based ASRCode1
Inner speech recognition through electroencephalographic signals0
Scaling Up Deliberation for Multilingual ASR0
Automatic Speech Recognition of Low-Resource Languages Based on Chukchi0
Comparison of Soft and Hard Target RNN-T Distillation for Large-scale ASR0
Streaming Punctuation for Long-form Dictation with Transformers0
CTC Alignments Improve Autoregressive Translation0
An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition0
Pronunciation Modeling of Foreign Words for Mandarin ASR by Considering the Effect of Language Transfer0
SpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder Based Speech-Text Pre-trainingCode0
Cloud-based Automatic Speech Recognition Systems for Southeast Asian Languages0
Damage Control During Domain Adaptation for Transducer Based Automatic Speech Recognition0
Synthetic Dataset Generation for Privacy-Preserving Machine Learning0
JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMTCode1
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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