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 14511500 of 6433 papers

TitleStatusHype
ÌròyìnSpeech: A multi-purpose Yorùbá Speech CorpusCode1
UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models0
The timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems0
Learning Multi-modal Representations by Watching Hundreds of Surgical Video LecturesCode1
Turning Whisper into Real-Time Transcription SystemCode4
Cascaded Cross-Modal Transformer for Request and Complaint Detection0
CIF-T: A Novel CIF-based Transducer Architecture for Automatic Speech Recognition0
On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer0
A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision QuantizationCode0
Adaptation of Whisper models to child speech recognitionCode1
Code-Switched Urdu ASR for Noisy Telephonic Environment using Data Centric Approach with Hybrid HMM and CNN-TDNNCode0
Integration of Frame- and Label-synchronous Beam Search for Streaming Encoder-decoder Speech Recognition0
Robust Automatic Speech Recognition via WavAugment Guided Phoneme Adversarial Training0
Boosting Punctuation Restoration with Data Generation and Reinforcement Learning0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition0
Exploring the Integration of Speech Separation and Recognition with Self-Supervised Learning Representation0
Modality Confidence Aware Training for Robust End-to-End Spoken Language Understanding0
Prompting Large Language Models with Speech Recognition Abilities0
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality ConversionCode0
Topic Identification For Spontaneous Speech: Enriching Audio Features With Embedded Linguistic InformationCode0
Transsion TSUP's speech recognition system for ASRU 2023 MADASR Challenge0
A Deep Dive into the Disparity of Word Error Rates Across Thousands of NPTEL MOOC VideosCode0
Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding0
Globally Normalising the Transducer for Streaming Speech Recognition0
MASR: Multi-label Aware Speech Representation0
Leveraging Visemes for Better Visual Speech Representation and Lip Reading0
Zero-shot Domain-sensitive Speech Recognition with Prompt-conditioning Fine-tuningCode1
OxfordVGG Submission to the EGO4D AV Transcription ChallengeCode6
ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and DevelopmentCode1
Adapting Large Language Model with Speech for Fully Formatted End-to-End Speech RecognitionCode8
Towards Stealthy Backdoor Attacks against Speech Recognition via Elements of SoundCode1
Model Adaptation for ASR in low-resource Indian Languages0
On the Sensitivity of Deep Load Disaggregation to Adversarial Attacks0
Towards Model-Size Agnostic, Compute-Free, Memorization-based Inference of Deep Learning0
Ed-Fed: A generic federated learning framework with resource-aware client selection for edge devices0
Representation Learning With Hidden Unit Clustering For Low Resource Speech Applications0
Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition0
Towards spoken dialect identification of Irish0
Exploring the Integration of Large Language Models into Automatic Speech Recognition Systems: An Empirical Study0
Personalization for BERT-based Discriminative Speech Recognition Rescoring0
Leveraging Pretrained ASR Encoders for Effective and Efficient End-to-End Speech Intent Classification and Slot Filling0
SummaryMixing: A Linear-Complexity Alternative to Self-Attention for Speech Recognition and UnderstandingCode0
Writer adaptation for offline text recognition: An exploration of neural network-based methodsCode0
Speech Diarization and ASR with GMM0
SparseVSR: Lightweight and Noise Robust Visual Speech Recognition0
Can Generative Large Language Models Perform ASR Error Correction?0
Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments0
Gammatonegram Representation for End-to-End Dysarthric Speech Processing Tasks: Speech Recognition, Speaker Identification, and Intelligibility AssessmentCode0
Online Hybrid CTC/Attention End-to-End Automatic Speech Recognition Architecture0
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness0
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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