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 57015750 of 6433 papers

TitleStatusHype
Synchronous Transformers for End-to-End Speech Recognition0
Syntactic and Semantic Features For Code-Switching Factored Language Models0
Syntactic annotation of spontaneous speech: application to call-center conversation data0
Synth2Aug: Cross-domain speaker recognition with TTS synthesized speech0
SynthASR: Unlocking Synthetic Data for Speech Recognition0
Synthesising Audio Adversarial Examples for Automatic Speech Recognition0
Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognition0
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition0
Synthetic Dataset Generation for Privacy-Preserving Machine Learning0
Synthetic Query Generation using Large Language Models for Virtual Assistants0
SynthVSR: Scaling Up Visual Speech Recognition With Synthetic Supervision0
Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition0
Systolic Arrays and Structured Pruning Co-design for Efficient Transformers in Edge Systems0
Tackling Sequence to Sequence Mapping Problems with Neural Networks0
Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks0
Tag and correct: high precision post-editing approach to correction of speech recognition errors0
Taiwanese Speech Recognition Based on Hybrid Deep Neural Network Architecture0
TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos0
TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline0
Talk, Don't Write: A Study of Direct Speech-Based Image Retrieval0
Talking to Your TV: Context-Aware Voice Search with Hierarchical Recurrent Neural Networks0
TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge0
Tamil Language Computing: the Present and the Future0
Tandem Multitask Training of Speaker Diarisation and Speech Recognition for Meeting Transcription0
探究端對端混合模型架構於華語語音辨識 (An Investigation of Hybrid CTC-Attention Modeling in Mandarin Speech Recognition)0
探究端對端語音辨識於發音檢測與診斷(Investigating on Computer-Assisted Pronunciation Training Leveraging End-to-End Speech Recognition Techniques)0
Targeted Adversarial Examples for Black Box Audio Systems0
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS0
Task-aware Warping Factors in Mask-based Speech Enhancement0
Task-dependent modulation of the visual sensory thalamus assists visual-speech recognition0
Task Lineages: Dialog State Tracking for Flexible Interaction0
Task-oriented Document-Grounded Dialog Systems by HLTPR@RWTH for DSTC9 and DSTC100
Task-Specific Audio Coding for Machines: Machine-Learned Latent Features Are Codes for That Machine0
TBD: Benchmarking and Analyzing Deep Neural Network Training0
Teach an all-rounder with experts in different domains0
Team Deep Mixture of Experts for Distributed Power Control0
Team MTS @ AutoMin 2021: An Overview of Existing Summarization Approaches and Comparison to Unsupervised Summarization Techniques0
Techniques for Feature Extraction In Speech Recognition System : A Comparative Study0
Techniques for Vocabulary Expansion in Hybrid Speech Recognition Systems0
Technology-Augmented Multilingual Communication Models: New Interaction Paradigms, Shifts in the Language Services Industry, and Implications for Training Programs0
TED-LIUM: an Automatic Speech Recognition dedicated corpus0
Temperature-Based Deep Boltzmann Machines0
Temporal Attention Augmented Transformer Hawkes Process0
Temporal Information Processing on Noisy Quantum Computers0
Temporal Multimodal Learning in Audiovisual Speech Recognition0
Temporal Order Preserved Optimal Transport-based Cross-modal Knowledge Transfer Learning for ASR0
Tencent-MVSE: A Large-Scale Benchmark Dataset for Multi-Modal Video Similarity Evaluation0
Tensor decomposition for minimization of E2E SLU model toward on-device processing0
Teochew-Wild: The First In-the-wild Teochew Dataset with Orthographic Annotations0
Text Alignment for Real-Time Crowd Captioning0
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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