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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 976–1000 of 3012 papers

TitleStatusHype
End-to-End Joint Target and Non-Target Speakers ASR—0
SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings—0
Advancing African-Accented Speech Recognition: Epistemic Uncertainty-Driven Data Selection for Generalizable ASR ModelsCode0
Streaming Speech-to-Confusion Network Speech Recognition—0
Explainability of Speech Recognition Transformers via Gradient-based Attention VisualizationCode0
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home—0
Adaptation and Optimization of Automatic Speech Recognition (ASR) for the Maritime Domain in the Field of VHF Communication—0
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili—0
SlothSpeech: Denial-of-service Attack Against Speech Recognition ModelsCode0
AfriNames: Most ASR models "butcher" African Names—0
Some voices are too common: Building fair speech recognition systems using the Common Voice dataset—0
Bypass Temporal Classification: Weakly Supervised Automatic Speech Recognition with Imperfect Transcripts—0
Simple yet Effective Code-Switching Language Identification with Multitask Pre-Training and Transfer Learning—0
Accurate and Structured Pruning for Efficient Automatic Speech Recognition—0
Zero-Shot Automatic Pronunciation Assessment—0
VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition—0
Towards Selection of Text-to-speech Data to Augment ASR Training—0
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers—0
Graph Neural Networks for Contextual ASR with the Tree-Constrained Pointer GeneratorCode0
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions—0
CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voice—0
Improving Textless Spoken Language Understanding with Discrete Units as Intermediate Target—0
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition—0
Building Accurate Low Latency ASR for Streaming Voice Search—0
DisfluencyFixer: A tool to enhance Language Learning through Speech To Speech Disfluency Correction—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