SOTAVerified

Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

Showing 451475 of 3012 papers

TitleStatusHype
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition SystemsCode0
AfriHuBERT: A self-supervised speech representation model for African languagesCode0
End to End ASR System with Automatic Punctuation InsertionCode0
Advancing African-Accented Speech Recognition: Epistemic Uncertainty-Driven Data Selection for Generalizable ASR ModelsCode0
AequeVox: Automated Fairness Testing of Speech Recognition SystemsCode0
ASDF: A Differential Testing Framework for Automatic Speech Recognition SystemsCode0
Effects of Layer Freezing on Transferring a Speech Recognition System to Under-resourced LanguagesCode0
Efficient Ensemble for Multimodal Punctuation Restoration using Time-Delay Neural NetworkCode0
Graph Neural Networks for Contextual ASR with the Tree-Constrained Pointer GeneratorCode0
RED-ACE: Robust Error Detection for ASR using Confidence EmbeddingsCode0
Analyzing the impact of speaker localization errors on speech separation for automatic speech recognitionCode0
Kurdish (Sorani) Speech to Text: Presenting an Experimental DatasetCode0
Does Joint Training Really Help Cascaded Speech Translation?Code0
Adversarial Training For Low-Resource Disfluency CorrectionCode0
DoCIA: An Online Document-Level Context Incorporation Agent for Speech TranslationCode0
Domain Specific Wav2vec 2.0 Fine-tuning For The SE&R 2022 ChallengeCode0
Discrete Speech Unit Extraction via Independent Component AnalysisCode0
ROSE: A Recognition-Oriented Speech Enhancement Framework in Air Traffic Control Using Multi-Objective LearningCode0
Are Neural Open-Domain Dialog Systems Robust to Speech Recognition Errors in the Dialog History? An Empirical StudyCode0
Discrete Cross-Modal Alignment Enables Zero-Shot Speech TranslationCode0
Self-supervised Speech Representations Still Struggle with African American Vernacular EnglishCode0
BERT Attends the Conversation: Improving Low-Resource Conversational ASRCode0
Arabic Speech Recognition by End-to-End, Modular Systems and HumanCode0
Semantic Mask for Transformer based End-to-End Speech RecognitionCode0
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European LanguagesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1Unverified
2TM-seq2seqTest WER9.7Unverified
3CTC/attentionTest WER8.2Unverified
4LF-MMI TDNNTest WER6.7Unverified
5Whisper-LLaMATest WER6.6Unverified
6End2end ConformerTest WER3.9Unverified
7End2end ConformerTest WER3.7Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7Unverified
9CTC/AttentionTest WER1.5Unverified
10WhisperTest WER1.3Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5Unverified
2CleanMel-L-maskCER14.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32Unverified
2Whisper-largev3-finetunedTest WER10.82Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98Unverified