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

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Showing 301–350 of 6433 papers

TitleStatusHype
Predicting Compact Phrasal Rewrites with Large Language Models for ASR Post Editing—0
Development of an Inclusive Educational Platform Using Open Technologies and Machine Learning: A Case Study on Accessibility Enhancement—0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
FlanEC: Exploring Flan-T5 for Post-ASR Error CorrectionCode1
A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data—0
Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audio—0
Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges—0
Enhancing Neural Spoken Language Recognition: An Exploration with Multilingual Datasets—0
A Benchmark of French ASR Systems Based on Error Severity—0
GEC-RAG: Improving Generative Error Correction via Retrieval-Augmented Generation for Automatic Speech Recognition Systems—0
Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR—0
Automatic Speech Recognition for Sanskrit with Transfer Learning—0
Teaching Wav2Vec2 the Language of the BrainCode0
PIER: A Novel Metric for Evaluating What Matters in Code-SwitchingCode0
Delayed Fusion: Integrating Large Language Models into First-Pass Decoding in End-to-end Speech Recognition—0
A Non-autoregressive Model for Joint STT and TTS—0
Adapting Whisper for Regional Dialects: Enhancing Public Services for Vulnerable Populations in the United Kingdom—0
persoDA: Personalized Data Augmentation for Personalized ASR—0
Selective Attention Merging for low resource tasks: A case study of Child ASRCode0
Loudspeaker Beamforming to Enhance Speech Recognition Performance of Voice Driven Applications—0
Joint Automatic Speech Recognition And Structure Learning For Better Speech UnderstandingCode0
Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model—0
AdaCS: Adaptive Normalization for Enhanced Code-Switching ASRCode0
Speech Recognition for Automatically Assessing Afrikaans and isiXhosa Preschool Oral Narratives—0
Discrete Speech Unit Extraction via Independent Component AnalysisCode0
A Survey on Spoken Italian Datasets and Corpora—0
TTS-Transducer: End-to-End Speech Synthesis with Neural Transducer—0
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language UnderstandingCode0
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI—0
Benchmarking Rotary Position Embeddings for Automatic Speech Recognition—0
Comparing Self-Supervised Learning Models Pre-Trained on Human Speech and Animal Vocalizations for Bioacoustics ProcessingCode0
Universal-2-TF: Robust All-Neural Text Formatting for ASR—0
Methods to Increase the Amount of Data for Speech Recognition for Low Resource Languages—0
LipGen: Viseme-Guided Lip Video Generation for Enhancing Visual Speech Recognition—0
Deep Learning for Pathological Speech: A Survey—0
Towards a Generalizable Speech Marker for Parkinson's Disease Diagnosis—0
Universal Speaker Embedding Free Target Speaker Extraction and Personal Voice Activity Detection—0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models—0
Listening and Seeing Again: Generative Error Correction for Audio-Visual Speech RecognitionCode0
Improving Transducer-Based Spoken Language Understanding with Self-Conditioned CTC and Knowledge Transfer—0
Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal ModelsCode0
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale—0
Breaking Through the Spike: Spike Window Decoding for Accelerated and Precise Automatic Speech Recognition—0
Automatic Text Pronunciation Correlation Generation and Application for Contextual Biasing—0
Large Language Models Are Read/Write Policy-Makers for Simultaneous GenerationCode1
Incremental Dialogue Management: Survey, Discussion, and Implications for HRI—0
Fotheidil: an Automatic Transcription System for the Irish Language—0
Whisper Turns Stronger: Augmenting Wav2Vec 2.0 for Superior ASR in Low-Resource Languages—0
DiCoW: Diarization-Conditioned Whisper for Target Speaker Automatic Speech RecognitionCode2
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization—0
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All datasetsLibriSpeech test-cleanLibriSpeech test-otherSwitchboard + Hub500TIMITAISHELL-1WSJ eval92Common Voice Germanswb_hub_500 WER fullSWBCHTUDACommon Voice FrenchCommon Voice SpanishMediaSpeech

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6—Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8—Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19—Unverified
4SnipsWord Error Rate (WER)6.4—Unverified
5Li-GRUWord Error Rate (WER)6.2—Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5—Unverified
7CTC + policy learningWord Error Rate (WER)5.42—Unverified
8Deep Speech 2Word Error Rate (WER)5.33—Unverified
9Gated ConvNetsWord Error Rate (WER)4.8—Unverified
10HMM-TDNN + iVectorsWord Error Rate (WER)4.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84—Unverified
2SnipsWord Error Rate (WER)16.5—Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28—Unverified
4Deep Speech 2Word Error Rate (WER)13.25—Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5—Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65—Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47—Unverified
8MT4SSLWord Error Rate (WER)9.6—Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79—Unverified
10EspressoWord Error Rate (WER)8.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20—Unverified
2DNN-HMMPercentage error18.5—Unverified
3CD-DNNPercentage error16.1—Unverified
4DNNPercentage error16—Unverified
5DNN + DropoutPercentage error15—Unverified
6DNN BMMIPercentage error12.9—Unverified
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9—Unverified
8DNN MPEPercentage error12.9—Unverified
9DNN MMIPercentage error12.9—Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage error12.6—Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2—Unverified
2LAS multitask with indicators samplingPercentage error20.4—Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1—Unverified
4QCNN-10L-256FMPercentage error19.64—Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7—Unverified
6Bi-RNN + AttentionPercentage error17.6—Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3—Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7—Unverified
9Light Gated Recurrent UnitsPercentage error16.7—Unverified
10GRUPercentage error16.6—Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7—Unverified
2CTC/AttWord Error Rate (WER)6.7—Unverified
3BRA-EWord Error Rate (WER)6.63—Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34—Unverified
5BATWord Error Rate (WER)4.97—Unverified
6ParaformerWord Error Rate (WER)4.95—Unverified
7U2Word Error Rate (WER)4.72—Unverified
8UMAWord Error Rate (WER)4.7—Unverified
9Lightweight TransducerWord Error Rate (WER)4.31—Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9—Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6—Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79—Unverified
4Deep Speech 2Word Error Rate (WER)3.6—Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6—Unverified
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5—Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)3.5—Unverified
8EspressoWord Error Rate (WER)3.4—Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2—Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19—Unverified