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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 2676–2700 of 3012 papers

TitleStatusHype
An Online Attention-based Model for Speech Recognition—0
A Novel End-to-End CAPT System for L2 Children Learners—0
A Novel Self-training Approach for Low-resource Speech Recognition—0
Anti-spoofing Methods for Automatic SpeakerVerification System—0
An Ultra-low Power RNN Classifier for Always-On Voice Wake-Up Detection Robust to Real-World Scenarios—0
An Unsupervised Speaker Clustering Technique based on SOM and I-vectors for Speech Recognition Systems—0
``Oh, I've Heard That Before'': Modelling Own-Dialect Bias After Perceptual Learning by Weighting Training Data—0
A Parallel Recurrent Neural Network for Language Modeling with POS Tags—0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System—0
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts—0
Applying LLMs for Rescoring N-best ASR Hypotheses of Casual Conversations: Effects of Domain Adaptation and Context Carry-over—0
ApproBiVT: Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff Guided Early Stopping and Checkpoint Averaging—0
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling—0
A practical two-stage training strategy for multi-stream end-to-end speech recognition—0
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students—0
A privacy-preserving method using secret key for convolutional neural network-based speech classification—0
A Probabilistic Framework for Representing Dialog Systems and Entropy-Based Dialog Management through Dynamic Stochastic State Evolution—0
Arabic Code-Switching Speech Recognition using Monolingual Data—0
Arabic Language WEKA-Based Dialect Classifier for Arabic Automatic Speech Recognition Transcripts—0
A Recorded Debating Dataset—0
Are disentangled representations all you need to build speaker anonymization systems?—0
Are Transformers in Pre-trained LM A Good ASR Encoder? An Empirical Study—0
A review of on-device fully neural end-to-end automatic speech recognition algorithms—0
Articulatory and bottleneck features for speaker-independent ASR of dysarthric speech—0
Articulatory Features for ASR of Pathological 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