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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

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Showing 351–375 of 3012 papers

TitleStatusHype
Exploring Generative Error Correction for Dysarthric Speech RecognitionCode0
KIT's Low-resource Speech Translation Systems for IWSLT2025: System Enhancement with Synthetic Data and Model Regularization—0
In-context Language Learning for Endangered Languages in Speech Recognition—0
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence—0
Robust fine-tuning of speech recognition models via model merging: application to disordered speech—0
CHSER: A Dataset and Case Study on Generative Speech Error Correction for Child ASRCode0
VietASR: Achieving Industry-level Vietnamese ASR with 50-hour labeled data and Large-Scale Speech Pretraining—0
LLM-based Generative Error Correction for Rare Words with Synthetic Data and Phonetic ContextCode0
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models—0
SoccerChat: Integrating Multimodal Data for Enhanced Soccer Game UnderstandingCode0
Large Language Models based ASR Error Correction for Child Conversations—0
In-Context Learning Boosts Speech Recognition via Human-like Adaptation to Speakers and Language Varieties—0
PersonaTAB: Predicting Personality Traits using Textual, Acoustic, and Behavioral Cues in Fully-Duplex Speech DialogsCode0
Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource LanguagesCode0
From Weak Labels to Strong Results: Utilizing 5,000 Hours of Noisy Classroom Transcripts with Minimal Accurate Data—0
LegoSLM: Connecting LLM with Speech Encoder using CTC Posteriors—0
ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems—0
Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio—0
Automatic Speech Recognition for African Low-Resource Languages: Challenges and Future Directions—0
Multi-Stage Speaker Diarization for Noisy ClassroomsCode0
LipDiffuser: Lip-to-Speech Generation with Conditional Diffusion Models—0
Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients—0
Teochew-Wild: The First In-the-wild Teochew Dataset with Orthographic Annotations—0
SepALM: Audio Language Models Are Error Correctors for Robust Speech Separation—0
Fairness of Automatic Speech Recognition in Cleft Lip and Palate Speech—0
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All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

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