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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 576–600 of 3012 papers

TitleStatusHype
A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting—0
ASR Rescoring and Confidence Estimation with ELECTRA—0
ASR is all you need: cross-modal distillation for lip reading—0
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews—0
ASR in German: A Detailed Error Analysis—0
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding—0
A Hierarchical Neural Model for Learning Sequences of Dialogue Acts—0
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition—0
ASR for Non-standardised Languages with Dialectal Variation: the case of Swiss German—0
ASR for Documenting Acutely Under-Resourced Indigenous Languages—0
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding—0
ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems—0
ASR error management for improving spoken language understanding—0
Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning—0
Acoustic Model Fusion for End-to-end Speech Recognition—0
Accent Recognition with Hybrid Phonetic Features—0
ASR Error Detection via Audio-Transcript entailment—0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking—0
ASR Error Correction using Large Language Models—0
ASR Error Correction and Domain Adaptation Using Machine Translation—0
A Generative Model of a Pronunciation Lexicon for Hindi—0
Acoustic Model Compression with MAP adaptation—0
ASR-EC Benchmark: Evaluating Large Language Models on Chinese ASR Error Correction—0
ASR Bundestag: A Large-Scale political debate dataset in German—0
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks—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