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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 2551–2575 of 3012 papers

TitleStatusHype
Stream attention-based multi-array end-to-end speech recognition—0
Reinforcement Learning Based Speech Enhancement for Robust Speech Recognition—0
Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling—0
Multimodal Grounding for Sequence-to-Sequence Speech RecognitionCode0
Confusion2Vec: Towards Enriching Vector Space Word Representations with Representational Ambiguities—0
CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments—0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—0
Bidirectional Quaternion Long-Short Term Memory Recurrent Neural Networks for Speech RecognitionCode0
Discriminative training of RNNLMs with the average word error criterion—0
When CTC Training Meets Acoustic Landmarks—0
End-to-End Monaural Multi-speaker ASR System without Pretraining—0
Leveraging Weakly Supervised Data to Improve End-to-End Speech-to-Text Translation—0
Adversarial Black-Box Attacks on Automatic Speech Recognition Systems using Multi-Objective Evolutionary Optimization—0
Improving the Robustness of Speech Translation—0
Cycle-consistency training for end-to-end speech recognition—0
Training Neural Speech Recognition Systems with Synthetic Speech Augmentation—0
Adversarial Training of End-to-end Speech Recognition Using a Criticizing Language Model—0
Introspection for convolutional automatic speech recognition—0
Sisyphus, a Workflow Manager Designed for Machine Translation and Automatic Speech Recognition—0
How2: A Large-scale Dataset for Multimodal Language UnderstandingCode1
Tropical Modeling of Weighted Transducer Algorithms on Graphs—0
End-to-End Feedback Loss in Speech Chain Framework via Straight-Through Estimator—0
Towards End-to-End Code-Switching Speech Recognition—0
Towards End-to-end Automatic Code-Switching Speech Recognition—0
Bi-Directional Lattice Recurrent Neural Networks for Confidence EstimationCode0
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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