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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 701–725 of 3012 papers

TitleStatusHype
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction—0
Radio2Text: Streaming Speech Recognition Using mmWave Radio Signals—0
Accurate synthesis of Dysarthric Speech for ASR data augmentation—0
End-to-End Open Vocabulary Keyword Search With Multilingual Neural RepresentationsCode0
Improving CTC-AED model with integrated-CTC and auxiliary loss regularization—0
Using Text Injection to Improve Recognition of Personal Identifiers in Speech—0
Text Injection for Capitalization and Turn-Taking Prediction in Speech Models—0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
Bilingual Streaming ASR with Grapheme units and Auxiliary Monolingual Loss—0
A Novel Self-training Approach for Low-resource Speech Recognition—0
Comparative Analysis of the wav2vec 2.0 Feature Extractor—0
OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data GenerationCode1
Boosting Chinese ASR Error Correction with Dynamic Error Scaling Mechanism—0
ApproBiVT: Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff Guided Early Stopping and Checkpoint Averaging—0
ÌròyìnSpeech: A multi-purpose Yorùbá Speech CorpusCode1
Cascaded Cross-Modal Transformer for Request and Complaint Detection—0
On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer—0
Adaptation of Whisper models to child speech recognitionCode1
A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision QuantizationCode0
Robust Automatic Speech Recognition via WavAugment Guided Phoneme Adversarial Training—0
Boosting Punctuation Restoration with Data Generation and Reinforcement Learning—0
Exploring the Integration of Speech Separation and Recognition with Self-Supervised Learning Representation—0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition—0
Prompting Large Language Models with Speech Recognition Abilities—0
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality ConversionCode0
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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