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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 101–150 of 3012 papers

TitleStatusHype
Automatic speech recognition for the Nepali language using CNN, bidirectional LSTM and ResNetCode1
Brazilian Portuguese Speech Recognition Using Wav2vec 2.0Code1
Can we use Common Voice to train a Multi-Speaker TTS system?Code1
Can Contextual Biasing Remain Effective with Whisper and GPT-2?Code1
AVLnet: Learning Audio-Visual Language Representations from Instructional VideosCode1
Adaptation of Whisper models to child speech recognitionCode1
Enhancing Multimodal Sentiment Analysis for Missing Modality through Self-Distillation and Unified Modality Cross-AttentionCode1
CL-MASR: A Continual Learning Benchmark for Multilingual ASRCode1
Adapting End-to-End Speech Recognition for Readable SubtitlesCode1
Automatic Disfluency Detection from Untranscribed SpeechCode1
Framework for Curating Speech Datasets and Evaluating ASR Systems: A Case Study for PolishCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
Combining Frame-Synchronous and Label-Synchronous Systems for Speech RecognitionCode1
EnCodecMAE: Leveraging neural codecs for universal audio representation learningCode1
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech RecognitionCode1
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language ModelsCode1
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer LearningCode1
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech RecognitionCode1
ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global ContextCode1
Consistent Training and Decoding For End-to-end Speech Recognition Using Lattice-free MMICode1
CopyNE: Better Contextual ASR by Copying Named EntitiesCode1
Improving RNN Transducer Based ASR with Auxiliary TasksCode1
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural NetworksCode1
Controlling Whisper: Universal Acoustic Adversarial Attacks to Control Speech Foundation ModelsCode1
indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languagesCode1
Continuous speech separation: dataset and analysisCode1
Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task LearningCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
End-to-end Named Entity Recognition from English SpeechCode1
Audio-Visual Efficient Conformer for Robust Speech RecognitionCode1
Accented Speech Recognition With Accent-specific CodebooksCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
Attentive Sequence-to-Sequence Learning for Diacritic Restoration of Yorùbá Language TextCode1
Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation ModelsCode1
End-to-End Speech Recognition and Disfluency RemovalCode1
ESB: A Benchmark For Multi-Domain End-to-End Speech RecognitionCode1
Attention-based Audio-Visual Fusion for Robust Automatic Speech RecognitionCode1
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applicationsCode1
Earnings-22: A Practical Benchmark for Accents in the WildCode1
A context-aware knowledge transferring strategy for CTC-based ASRCode1
A transfer learning based approach for pronunciation scoringCode1
Attention-based Contextual Language Model Adaptation for Speech RecognitionCode1
Efficient Adapter Transfer of Self-Supervised Speech Models for Automatic Speech RecognitionCode1
A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and EnglishCode1
A Survey on Non-Autoregressive Generation for Neural Machine Translation and BeyondCode1
ASR Error Correction with Constrained Decoding on Operation PredictionCode1
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
Dual-Path Style Learning for End-to-End Noise-Robust Speech RecognitionCode1
DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question AnsweringCode1
Advancing Test-Time Adaptation in Wild Acoustic Test SettingsCode1
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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