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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 1301–1350 of 3012 papers

TitleStatusHype
Cantonese Automatic Speech Recognition Using Transfer Learning from Mandarin—0
Generative error correction for code-switching speech recognition using large language models—0
Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter—0
Gesture-Aware Zero-Shot Speech Recognition for Patients with Language Disorders—0
Fast and Robust Unsupervised Contextual Biasing for Speech Recognition—0
A Wav2vec2-Based Experimental Study on Self-Supervised Learning Methods to Improve Child Speech Recognition—0
Arabic Language WEKA-Based Dialect Classifier for Arabic Automatic Speech Recognition Transcripts—0
Fast and Accurate OOV Decoder on High-Level Features—0
Fast and Accurate Capitalization and Punctuation for Automatic Speech Recognition Using Transformer and Chunk Merging—0
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages—0
Falling silent, lost for words ... Tracing personal involvement in interviews with Dutch war veterans—0
Calibration of Phone Likelihoods in Automatic Speech Recognition—0
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition—0
Graph based manifold regularized deep neural networks for automatic speech recognition—0
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy—0
AccentDB: A Database of Non-Native English Accents to Assist Neural Speech Recognition—0
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder—0
Fairness of Automatic Speech Recognition in Cleft Lip and Palate Speech—0
FairLENS: Assessing Fairness in Law Enforcement Speech Recognition—0
Calibrate and Refine! A Novel and Agile Framework for ASR-error Robust Intent Detection—0
Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation—0
Failing Forward: Improving Generative Error Correction for ASR with Synthetic Data and Retrieval Augmentation—0
Hallucination of speech recognition errors with sequence to sequence learning—0
Hallucinations in Neural Automatic Speech Recognition: Identifying Errors and Hallucinatory Models—0
Hard Sample Mining for the Improved Retraining of Automatic Speech Recognition—0
Hard-Synth: Synthesizing Diverse Hard Samples for ASR using Zero-Shot TTS and LLM—0
Harnessing the Zero-Shot Power of Instruction-Tuned Large Language Model in End-to-End Speech Recognition—0
Harnessing Transfer Learning from Swahili: Advancing Solutions for Comorian Dialects—0
HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition—0
Head-synchronous Decoding for Transformer-based Streaming ASR—0
Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems—0
Hear No Evil: Towards Adversarial Robustness of Automatic Speech Recognition via Multi-Task Learning—0
HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing—0
HENT-SRT: Hierarchical Efficient Neural Transducer with Self-Distillation for Joint Speech Recognition and Translation—0
HESITA(te) in Portuguese—0
Heterogeneous Language Model Optimization in Automatic Speech Recognition—0
Heterogeneous Reservoir Computing Models for Persian Speech Recognition—0
Hey ASR System! Why Aren't You More Inclusive? Automatic Speech Recognition Systems' Bias and Proposed Bias Mitigation Techniques. A Literature Review—0
Hierarchical Conditional End-to-End ASR with CTC and Multi-Granular Subword Units—0
Hierarchical Cross-Modality Knowledge Transfer with Sinkhorn Attention for CTC-based ASR—0
Factual Consistency Oriented Speech Recognition—0
Hierarchical Sequence to Sequence Voice Conversion with Limited Data—0
CAFE A Novel Code switching Dataset for Algerian Dialect French and English—0
Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation—0
Arabic Code-Switching Speech Recognition using Monolingual Data—0
Highland Puebla Nahuatl Speech Translation Corpus for Endangered Language Documentation—0
Facetron: A Multi-speaker Face-to-Speech Model based on Cross-modal Latent Representations—0
High-precision Voice Search Query Correction via Retrievable Speech-text Embedings—0
Hindi-English Code-Switching Speech Corpus—0
Byte Pair Encoding Is All You Need For Automatic Bengali Speech Recognition—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