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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 201–250 of 3012 papers

TitleStatusHype
A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and EnglishCode1
USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition ExperimentsCode1
The History of Speech Recognition to the Year 2030Code1
Brazilian Portuguese Speech Recognition Using Wav2vec 2.0Code1
Token-Level Supervised Contrastive Learning for Punctuation RestorationCode1
STRODE: Stochastic Boundary Ordinary Differential EquationCode1
A Comparison of Methods for OOV-word Recognition on a New Public DatasetCode1
Layer-wise Analysis of a Self-supervised Speech Representation ModelCode1
TENET: A Time-reversal Enhancement Network for Noise-robust ASRCode1
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech RecognitionCode1
Combining Frame-Synchronous and Label-Synchronous Systems for Speech RecognitionCode1
Golos: Russian Dataset for Speech ResearchCode1
Learning Audio-Visual DereverberationCode1
Incorporating External POS Tagger for Punctuation RestorationCode1
Lightweight Adapter Tuning for Multilingual Speech TranslationCode1
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling InsightsCode1
Attention-based Contextual Language Model Adaptation for Speech RecognitionCode1
Investigating the Reordering Capability in CTC-based Non-Autoregressive End-to-End Speech TranslationCode1
End-to-End Speech Recognition from Federated Acoustic ModelsCode1
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from SpeechCode1
A Toolbox for Construction and Analysis of Speech DatasetsCode1
RNN Transducer Models For Spoken Language UnderstandingCode1
Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible InputsCode1
ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of KaldiCode1
Multilingual and code-switching ASR challenges for low resource Indian languagesCode1
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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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