Recognition of vehicle license plates in highway scenes with deep fusion network and connectionist temporal classification [PDF]
IET Image ProcessingLicense plate recognition is crucial in Intelligent Transportation Systems (ITS) for vehicle management, traffic monitoring, and security inspection.
Liru Hua +5 more
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End-to-End Automatic Pronunciation Error Detection Based on Improved Hybrid CTC/Attention Architecture [PDF]
Sensors, 2020 Advanced automatic pronunciation error detection (APED) algorithms are usually based on state-of-the-art automatic speech recognition (ASR) techniques. With the development of deep learning technology, end-to-end ASR technology has gradually matured and ...
Long Zhang +7 more
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Focal CTC Loss for Chinese Optical Character Recognition on Unbalanced Datasets [PDF]
Complexity, 2019 In this paper, we propose a novel deep model for unbalanced distribution Character Recognition by employing focal loss based connectionist temporal classification (CTC) function.
Xinjie Feng +2 more
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Improving Hybrid CTC/Attention Architecture with Time-Restricted Self-Attention CTC for End-to-End Speech Recognition [PDF]
Applied Sciences, 2019 As demonstrated in hybrid connectionist temporal classification (CTC)/Attention architecture, joint training with a CTC objective is very effective to solve the misalignment problem existing in the attention-based end-to-end automatic speech recognition (
Long Wu, Ta Li, Li Wang, Yonghong Yan
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Context Conditioning via Surrounding Predictions for Non-Recurrent CTC Models
IEEE Access, 2023 Connectionist Temporal Classification (CTC) loss has become widely used in sequence modeling tasks such as Automatic Speech Recognition (ASR) and Handwritten Text Recognition (HTR) due to its ease of use.
Burin Naowarat +2 more
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Recognition of English speech – using a deep learning algorithm
Journal of Intelligent Systems, 2023 The accurate recognition of speech is beneficial to the fields of machine translation and intelligent human–computer interaction. After briefly introducing speech recognition algorithms, this study proposed to recognize speech with a recurrent neural ...
Wang Shuyan
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A Helium Speech Unscrambling Algorithm Based on Deep Learning
Information, 2023 Helium speech, the language spoken by divers in the deep sea who breathe a high-pressure helium–oxygen mixture, is almost unintelligible. To accurately unscramble helium speech, a neural network based on deep learning is proposed.
Yonghong Chen, Shibing Zhang
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CTC Variations Through New WFST Topologies [PDF]
, 2022 This paper presents novel Weighted Finite-State Transducer (WFST) topologies to implement Connectionist Temporal Classification (CTC)-like algorithms for automatic speech recognition.
Laptev, Aleksandr +2 more
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Automatic Speech Recognition Method Based on Deep Learning Approaches for Uzbek Language
Sensors, 2022 Communication has been an important aspect of human life, civilization, and globalization for thousands of years. Biometric analysis, education, security, healthcare, and smart cities are only a few examples of speech recognition applications.
Abdinabi Mukhamadiyev +3 more
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JSUM: A Multitask Learning Speech Recognition Model for Jointly Supervised and Unsupervised Learning
Applied Sciences, 2023 In recent years, the end-to-end speech recognition model has emerged as a popular alternative to the traditional Deep Neural Network—Hidden Markov Model (DNN-HMM).
Nurmemet Yolwas, Weijing Meng
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