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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 801–825 of 3012 papers

TitleStatusHype
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models—0
CTC-DRO: Robust Optimization for Reducing Language Disparities in Speech Recognition—0
Alignment-Free Training for Transducer-based Multi-Talker ASR—0
CTC Variations Through New WFST Topologies—0
Cumulative Adaptation for BLSTM Acoustic Models—0
CUNI Neural ASR with Phoneme-Level Intermediate Step for -Native at IWSLT 2020—0
Corpus Phonetics Tutorial—0
Cycle-consistency training for end-to-end speech recognition—0
Cycle-Consistent GAN Front-End to Improve ASR Robustness to Perturbed Speech—0
Corpus Generation for Voice Command in Smart Home and the Effect of Speech Synthesis on End-to-End SLU—0
Attention-based ASR with Lightweight and Dynamic Convolutions—0
Corpora for Cross-Language Information Retrieval in Six Less-Resourced Languages—0
CORILGA: a Galician Multilevel Annotated Speech Corpus for Linguistic Analysis—0
Alignment Entropy Regularization—0
Data Augmentation for End-to-end Code-switching Speech Recognition—0
Data Augmentation for End-to-End Speech Translation: FBK@IWSLT ‘19—0
Data Augmentation for Low-Resource Quechua ASR Improvement—0
Data Augmentation for Training Dialog Models Robust to Speech Recognition Errors—0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition—0
A CLARIN Transcription Portal for Interview Data—0
Data Augmentation with Locally-time Reversed Speech for Automatic Speech Recognition—0
Improving Speech Emotion Recognition with Unsupervised Speaking Style Transfer—0
3-D Feature and Acoustic Modeling for Far-Field Speech Recognition—0
Data-Driven Pronunciation Modeling of Swiss German Dialectal Speech for Automatic Speech Recognition—0
On the Problem of Text-To-Speech Model Selection for Synthetic Data Generation in Automatic 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