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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 1476–1500 of 3012 papers

TitleStatusHype
Improving Punctuation Restoration for Speech Transcripts via External Data—0
Improving Rare Words Recognition through Homophone Extension and Unified Writing for Low-resource Cantonese Speech Recognition—0
Improving Readability for Automatic Speech Recognition Transcription—0
An Investigation of Hybrid architectures for Low Resource Multilingual Speech Recognition system in Indian context—0
Improving RNN-T ASR Performance with Date-Time and Location Awareness—0
Enhancing Large Language Model-based Speech Recognition by Contextualization for Rare and Ambiguous Words—0
Continual Learning for On-Device Speech Recognition using Disentangled Conformers—0
Improving RNN transducer with normalized jointer network—0
Improving Robustness of Neural Inverse Text Normalization via Data-Augmentation, Semi-Supervised Learning, and Post-Aligning Method—0
Improving Scheduled Sampling for Neural Transducer-based ASR—0
Enhancing Indonesian Automatic Speech Recognition: Evaluating Multilingual Models with Diverse Speech Variabilities—0
Catch Me If You Can: Blackbox Adversarial Attacks on Automatic Speech Recognition using Frequency Masking—0
Random Utterance Concatenation Based Data Augmentation for Improving Short-video Speech Recognition—0
Improving Speech-based Emotion Recognition with Contextual Utterance Analysis and LLMs—0
Improving Speech Recognition for African American English With Audio Classification—0
Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives—0
Improving speech recognition models with small samples for air traffic control systems—0
Improving Speech Recognition on Noisy Speech via Speech Enhancement with Multi-Discriminators CycleGAN—0
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses—0
Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data—0
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies—0
Improving Streaming Transformer Based ASR Under a Framework of Self-supervised Learning—0
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus—0
Enhancing Documentation of Hupa with Automatic Speech Recognition—0
Enhancing Dialogue Speech Recognition with Robust Contextual Awareness via Noise Representation Learning—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