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Multilingual end-to-end ASR for low-resource Turkic languages with common alphabets. [PDF]

Sci Rep
Bekarystankyzy A, Mamyrbayev O, Mendes M, Fazylzhanova A, Assam M.   +4 more
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Speechformer-CTC: Sequential Modeling of Depression Detection with Speech Temporal Classification. [PDF]

Speech Commun
Wang J, Ravi V, Flint J, Alwan A.
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Tibetan-Chinese speech-to-speech translation based on discrete units. [PDF]

Sci Rep
Gong Z, Xu X, Zhao Y.
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Motif caller for sequence reconstruction in motif-based DNA storage. [PDF]

Sci Rep
Agarwal P, Pinnamaneni N, Heinis T.
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A Two-Level Illumination Correction Network for Digital Meter Reading Recognition in Non-Uniform Low-Light Conditions. [PDF]

J Imaging
Fu H, Xie Z, Jiang W, Ma X, Yang D.
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Leveraging object detection for early diagnosis of neurodegenerative diseases through radiomic analysis. [PDF]

Front Aging Neurosci
Zhi W, Liu Z, Huang L, Li M, Xu X, Xi Z.
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Impact of Natural Language Processing models on diagnosis and decision-making in healthcare, business, education, and sports: a review. [PDF]

Front Artif Intell
Choudhary A, Pamidimokkala S, R K, R M B.   +3 more
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Bream: an open-source deep learning framework for simultaneous base calling and DNA methylation detection on novel nanopore sequencing platforms. [PDF]

Front Genet
Yao HC, Wu B, Ye CL, Bai X, Chen HX, Hu G, Xiao CL.   +6 more
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NeuroQ: Quantum-Inspired Brain Emulation. [PDF]

Biomimetics (Basel)
Vallverdú J, Rius G.
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Variational Connectionist Temporal Classification

Lecture Notes in Computer Science, 2020
Connectionist Temporal Classification (CTC) is a training criterion designed for sequence labelling problems where the alignment between the inputs and the target labels is unknown. One of the key steps is to add a blank symbol to the target vocabulary. However, CTC tends to output spiky distributions since it prefers to output blank symbol most of the
Jingdong Chen, Chen Jingdong
exaly   +3 more sources