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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1151–1175 of 3012 papers

TitleStatusHype
Improving Mandarin Speech Recogntion with Block-augmented TransformerCode1
ASR Error Detection via Audio-Transcript entailment—0
Improving Data Driven Inverse Text Normalization using Data Augmentation—0
When Is TTS Augmentation Through a Pivot Language Useful?Code0
Transfer Learning of wav2vec 2.0 for Automatic Lyric TranscriptionCode1
ESPnet-SE++: Speech Enhancement for Robust Speech Recognition, Translation, and Understanding—0
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale—0
End-to-End Spoken Language Understanding: Performance analyses of a voice command task in a low resource setting—0
Reducing Geographic Disparities in Automatic Speech Recognition via Elastic Weight Consolidation—0
Direction-Aware Joint Adaptation of Neural Speech Enhancement and Recognition in Real Multiparty Conversational Environments—0
Deep versus Wide: An Analysis of Student Architectures for Task-Agnostic Knowledge Distillation of Self-Supervised Speech Models—0
Data Augmentation for Low-Resource Quechua ASR Improvement—0
MM-ALT: A Multimodal Automatic Lyric Transcription SystemCode1
Huqariq: A Multilingual Speech Corpus of Native Languages of Peru for Speech Recognition—0
End-to-end speech recognition modeling from de-identified data—0
Online Continual Learning of End-to-End Speech Recognition Models—0
pMCT: Patched Multi-Condition Training for Robust Speech Recognition—0
Speaker Anonymization with Phonetic Intermediate Representations—0
Investigating the Impact of Cross-lingual Acoustic-Phonetic Similarities on Multilingual Speech Recognition—0
End-to-end Speech-to-Punctuated-Text Recognition—0
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies—0
Compute Cost Amortized Transformer for Streaming ASR—0
Vietnamese Capitalization and Punctuation Recovery ModelsCode0
Leveraging Acoustic Contextual Representation by Audio-textual Cross-modal Learning for Conversational ASR—0
Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition—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