SOTAVerified

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

Showing 226250 of 3012 papers

TitleStatusHype
Integer-only Zero-shot Quantization for Efficient Speech RecognitionCode1
Leveraging pre-trained representations to improve access to untranscribed speech from endangered languagesCode1
Radically Old Way of Computing Spectra: Applications in End-to-End ASRCode1
Fast Development of ASR in African Languages using Self Supervised Speech Representation LearningCode1
WaveGuard: Understanding and Mitigating Audio Adversarial ExamplesCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
Transformer Language Models with LSTM-based Cross-utterance Information RepresentationCode1
An Investigation of End-to-End Models for Robust Speech RecognitionCode1
Dompteur: Taming Audio Adversarial ExamplesCode1
BembaSpeech: A Speech Recognition Corpus for the Bemba LanguageCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
AV Taris: Online Audio-Visual Speech RecognitionCode1
metaCAT: A Metadata-based Task-oriented Chatbot Annotation ToolCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
Improving RNN Transducer Based ASR with Auxiliary TasksCode1
Minimum Bayes Risk Training for End-to-End Speaker-Attributed ASRCode1
Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech TranslationCode1
Punctuation Restoration using Transformer Models for High-and Low-Resource LanguagesCode1
Joint Masked CPC and CTC Training for ASRCode1
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech RecognitionCode1
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech RecognitionCode1
Pushing the Limits of Semi-Supervised Learning for Automatic Speech RecognitionCode1
Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An OverviewCode1
Representation Learning for Sequence Data with Deep Autoencoding Predictive ComponentsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1Unverified
2TM-seq2seqTest WER9.7Unverified
3CTC/attentionTest WER8.2Unverified
4LF-MMI TDNNTest WER6.7Unverified
5Whisper-LLaMATest WER6.6Unverified
6End2end ConformerTest WER3.9Unverified
7End2end ConformerTest WER3.7Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7Unverified
9CTC/AttentionTest WER1.5Unverified
10WhisperTest WER1.3Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5Unverified
2CleanMel-L-maskCER14.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32Unverified
2Whisper-largev3-finetunedTest WER10.82Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98Unverified