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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 301–325 of 3012 papers

TitleStatusHype
A Deep Generative Acoustic Model for Compositional Automatic Speech Recognition—0
A comparison of end-to-end models for long-form speech recognition—0
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models—0
An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcripts—0
Transformer-based Cascaded Multimodal Speech Translation—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
ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers—0
ASTRA: Aligning Speech and Text Representations for Asr without Sampling—0
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features—0
An Effective Context-Balanced Adaptation Approach for Long-Tailed Speech Recognition—0
A bandit approach to curriculum generation for automatic speech recognition—0
An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution—0
Adaptive Sparse and Monotonic Attention for Transformer-based Automatic Speech Recognition—0
Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation—0
Assessing the Performance of Automatic Speech Recognition Systems When Used by Native and Non-Native Speakers of Three Major Languages in Dictation Workflows—0
An Audio-enriched BERT-based Framework for Spoken Multiple-choice Question Answering—0
An Attentional Model for Speech Translation Without Transcription—0
Adaptive Multi-Corpora Language Model Training for Speech Recognition—0
Anatomy of Industrial Scale Multilingual ASR—0
An ASR-free Fluency Scoring Approach with Self-Supervised Learning—0
Adaptive Frequency Cepstral Coefficients for Word Mispronunciation Detection—0
A Comparative Study on Speaker-attributed Automatic Speech Recognition in Multi-party Meetings—0
Assessing the Tolerance of Neural Machine Translation Systems Against Speech Recognition Errors—0
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech—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