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 101150 of 6433 papers

TitleStatusHype
MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text TranslationCode2
NusaCrowd: Open Source Initiative for Indonesian NLP ResourcesCode2
BLASER: A Text-Free Speech-to-Speech Translation Evaluation MetricCode2
Towards A Unified Conformer Structure: from ASR to ASV TaskCode2
Liquid Structural State-Space ModelsCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled ModalityCode2
TEVR: Improving Speech Recognition by Token Entropy Variance ReductionCode2
SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic LearningCode2
A New Frontier of AI: On-Device AI Training and PersonalizationCode2
Squeezeformer: An Efficient Transformer for Automatic Speech RecognitionCode2
Vakyansh: ASR Toolkit for Low Resource Indic languagesCode2
4-bit Conformer with Native Quantization Aware Training for Speech RecognitionCode2
CMGAN: Conformer-based Metric GAN for Speech EnhancementCode2
ICASSP 2022 Acoustic Echo Cancellation ChallengeCode2
Visual Speech Recognition for Multiple Languages in the WildCode2
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster PredictionCode2
Robust Self-Supervised Audio-Visual Speech RecognitionCode2
Automated Deep Learning: Neural Architecture Search Is Not the EndCode2
LightSeq2: Accelerated Training for Transformer-based Models on GPUsCode2
CrypTen: Secure Multi-Party Computation Meets Machine LearningCode2
VoiceFilter-Lite: Streaming Targeted Voice Separation for On-Device Speech RecognitionCode2
Fast Transformers with Clustered AttentionCode2
audino: A Modern Annotation Tool for Audio and SpeechCode2
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram MaskingCode2
Training RNNs as Fast as CNNsCode2
Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across ModalitiesCode1
From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech RecognitionCode1
Whisper-LM: Improving ASR Models with Language Models for Low-Resource LanguagesCode1
MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech TokensCode1
Whisper Speaker Identification: Leveraging Pre-Trained Multilingual Transformers for Robust Speaker EmbeddingsCode1
Zero-AVSR: Zero-Shot Audio-Visual Speech Recognition with LLMs by Learning Language-Agnostic Speech RepresentationsCode1
DuplexMamba: Enhancing Real-time Speech Conversations with Duplex and Streaming CapabilitiesCode1
VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR IdentificationCode1
Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation ModelsCode1
Sagalee: an Open Source Automatic Speech Recognition Dataset for Oromo LanguageCode1
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech RepresentationCode1
FlanEC: Exploring Flan-T5 for Post-ASR Error CorrectionCode1
Large Language Models Are Read/Write Policy-Makers for Simultaneous GenerationCode1
MathSpeech: Leveraging Small LMs for Accurate Conversion in Mathematical Speech-to-FormulaCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack DetectionCode1
Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual InputsCode1
STTATTS: Unified Speech-To-Text And Text-To-Speech ModelCode1
VoiceTextBlender: Augmenting Large Language Models with Speech Capabilities via Single-Stage Joint Speech-Text Supervised Fine-TuningCode1
AlignVSR: Audio-Visual Cross-Modal Alignment for Visual Speech RecognitionCode1
Enhancing Multimodal Sentiment Analysis for Missing Modality through Self-Distillation and Unified Modality Cross-AttentionCode1
EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation LearningCode1
VHASR: A Multimodal Speech Recognition System With Vision HotwordsCode1
Mamba for Streaming ASR Combined with Unimodal AggregationCode1
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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