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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 851–875 of 3012 papers

TitleStatusHype
Security and Privacy Problems in Voice Assistant Applications: A Survey—0
Multimodal Short Video Rumor Detection System Based on Contrastive Learning—0
Political corpus creation through automatic speech recognition on EU debatesCode0
A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers—0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition—0
Speech Reconstruction from Silent Tongue and Lip Articulation By Pseudo Target Generation and Domain Adversarial Training—0
Wav2code: Restore Clean Speech Representations via Codebook Lookup for Noise-Robust ASR—0
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data—0
Self-Supervised Learning-Based Source Separation for Meeting Data—0
Improving the previous state-of-the-art Frisian ASR by fine-tuning XLS-R—0
The Edinburgh International Accents of English Corpus: Towards the Democratization of English ASR—0
PROCTER: PROnunciation-aware ConTextual adaptER for personalized speech recognition in neural transducers—0
Joint unsupervised and supervised learning for context-aware language identification—0
Text is All You Need: Personalizing ASR Models using Controllable Speech Synthesis—0
Auto-AVSR: Audio-Visual Speech Recognition with Automatic LabelsCode2
Enhancing Unsupervised Speech Recognition with Diffusion GANs—0
Beyond Universal Transformer: block reusing with adaptor in Transformer for automatic speech recognition—0
Code-Switching Text Generation and Injection in Mandarin-English ASR—0
Knowledge Distillation from Multiple Foundation Models for End-to-End Speech Recognition—0
A Deep Learning System for Domain-specific Speech Recognition—0
Visual Information Matters for ASR Error Correction—0
DistillW2V2: A Small and Streaming Wav2vec 2.0 Based ASR Model—0
Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken SentencesCode0
HYBRIDFORMER: improving SqueezeFormer with hybrid attention and NSR mechanismCode0
Improving Accented Speech Recognition with Multi-Domain Training—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