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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 2501–2525 of 3012 papers

TitleStatusHype
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy—0
A Corpus and Phonetic Dictionary for Tunisian Arabic Speech Recognition—0
A Corpus for Modeling Word Importance in Spoken Dialogue Transcripts—0
A Corpus of Read and Spontaneous Upper Saxon German Speech for ASR Evaluation—0
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition—0
Acoustic and Textual Data Augmentation for Improved ASR of Code-Switching Speech—0
Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition—0
Acoustic Model Compression with MAP adaptation—0
Acoustic Model Fusion for End-to-end Speech Recognition—0
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition—0
Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation—0
Acoustic-Phonetic Approach for ASR of Less Resourced Languages Using Monolingual and Cross-Lingual Information—0
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages—0
Acoustics-guided evaluation (AGE): a new measure for estimating performance of speech enhancement algorithms for robust ASR—0
Acoustic to Articulatory Inversion of Speech; Data Driven Approaches, Challenges, Applications, and Future Scope—0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning—0
Acoustic Word Disambiguation with Phonogical Features in Danish ASR—0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition—0
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition—0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms—0
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition—0
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications—0
ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio—0
Adam^+: A Stochastic Method with Adaptive Variance Reduction—0
AdaMER-CTC: Connectionist Temporal Classification with Adaptive Maximum Entropy Regularization for Automatic 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