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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 576–600 of 3012 papers

TitleStatusHype
BayesSpeech: A Bayesian Transformer Network for Automatic Speech Recognition—0
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction—0
An efficient text augmentation approach for contextualized Mandarin speech recognition—0
A deep-learning based native-language classification by using a latent semantic analysis for the NLI Shared Task 2017—0
Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition—0
Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words—0
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems—0
BAT: Boundary aware transducer for memory-efficient and low-latency ASR—0
An Efficient and Effective Online Sentence Segmenter for Simultaneous Interpretation—0
A Deep Generative Acoustic Model for Compositional Automatic Speech Recognition—0
BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR—0
BART based semantic correction for Mandarin automatic speech recognition system—0
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models—0
Bangla-Wave: Improving Bangla Automatic Speech Recognition Utilizing N-gram Language Models—0
BanglaNum -- A Public Dataset for Bengali Digit Recognition from Speech—0
An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcripts—0
Back-Translation-Style Data Augmentation for End-to-End ASR—0
Babler - Data Collection from the Web to Support Speech Recognition and Keyword Search—0
An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement—0
An Effective End-to-End Modeling Approach for Mispronunciation Detection—0
A comparison of end-to-end models for long-form speech recognition—0
A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers—0
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features—0
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard—0
AV-CPL: Continuous Pseudo-Labeling for Audio-Visual 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