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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 1126–1150 of 3012 papers

TitleStatusHype
Using Kaldi for Automatic Speech Recognition of Conversational Austrian German—0
Multi-resolution location-based training for multi-channel continuous speech separation—0
Streaming Punctuation: A Novel Punctuation Technique Leveraging Bidirectional Context for Continuous Speech Recognition—0
Memory Augmented Lookup Dictionary based Language Modeling for Automatic Speech Recognition—0
Don't Be So Sure! Boosting ASR Decoding via Confidence Relaxation—0
Alignment Entropy Regularization—0
4D ASR: Joint modeling of CTC, Attention, Transducer, and Mask-Predict decoders—0
End-to-End Automatic Speech Recognition model for the Sudanese Dialect—0
Mu^2SLAM: Multitask, Multilingual Speech and Language Models—0
Fast Entropy-Based Methods of Word-Level Confidence Estimation for End-To-End Automatic Speech Recognition—0
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
Speech Aware Dialog System Technology Challenge (DSTC11)—0
Context-aware Fine-tuning of Self-supervised Speech Models—0
Improving Fast-slow Encoder based Transducer with Streaming Deliberation—0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction—0
Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator—0
End-to-End Speech Translation of Arabic to English Broadcast News—0
Improved Speech Pre-Training with Supervision-Enhanced Acoustic Unit—0
Improved Self-Supervised Multilingual Speech Representation Learning Combined with Auxiliary Language Information—0
Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers—0
Progressive Multi-Scale Self-Supervised Learning for Speech Recognition—0
Unsupervised Fine-Tuning Data Selection for ASR Using Self-Supervised Speech Models—0
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition—0
Continual Learning for On-Device Speech Recognition using Disentangled Conformers—0
Preliminary Study on SSCF-derived Polar Coordinate for ASR—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