Results 31 to 40 of about 76,886 (181)
Decode Jurnal Pendidikan Teknologi Informasi, 2023 Pengolahan informasi sebagai bentuk dari pengembangan teknologi yang semakin pesat adalah pengenalan tulisan tangan. Pengenalan tulisan tangan saat ini banyak diimplementasikan untuk melakukan identifikasi dokumen-dokumen penting berbentuk digital ...
Diana Tri Susetianingtias +5 more
semanticscholar +1 more source
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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American Sign Language Alphabet Recognition Using Inertial Motion Capture System with Deep Learning
Inventions, 2022 Sign language is designed as a natural communication method for the deaf community to convey messages and connect with society. In American sign language, twenty-six special sign gestures from the alphabet are used for the fingerspelling of proper words.
Yutong Gu +5 more
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Applied Sciences, 2021 We solve the problem of how to densely align actions in videos at frame level, with only the order of occurring actions available, in order to save the time-consuming efforts to accurately annotate the temporal boundaries of each action. We propose three
Lin Wang +3 more
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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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Towards multilingual end‐to‐end speech recognition for air traffic control
IET Intelligent Transport Systems, 2021 In this work, an end‐to‐end framework is proposed to achieve multilingual automatic speech recognition (ASR) in air traffic control (ATC) systems. Considering the standard ATC procedure, a recurrent neural network (RNN) based framework is selected to ...
Yi Lin, Bo Yang, Dongyue Guo, Peng Fan
doaj +1 more source
AdaMER-CTC: Connectionist Temporal Classification with Adaptive Maximum Entropy Regularization for Automatic Speech Recognition [PDF]
IEEE International Conference on Acoustics, Speech, and Signal ProcessingIn Automatic Speech Recognition (ASR) systems, a recurring obstacle is the generation of narrowly focused output distributions. This phenomenon emerges as a side effect of Connectionist Temporal Classification (CTC), a robust sequence learning tool that ...
Soohwan Eom +5 more
semanticscholar +1 more source
CTCModel: a Keras Model for Connectionist Temporal Classification
CoRR, 2019 We report an extension of a Keras Model, called CTCModel, to perform the Connectionist Temporal Classification (CTC) in a transparent way. Combined with Recurrent Neural Networks, the Connectionist Temporal Classification is the reference method for dealing with unsegmented input sequences, i.e.
Yann Soullard +2 more
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Local Self-Attention based Connectionist Temporal Classification for Speech Recognition
Computer Science & Information Technology (CS & IT), 2020 Deng Huizhen, Zhang zhaogong
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Mandarin recognition and improvement based on CTC criterion [PDF]
Jisuanji gongcheng, 2019 The cross-entropy criterion of mainstream neural network training classifies and optimizes each frame of acoustic data, while the continuous speech recognition uses the sequence-level transcription accuracy as the performance measurement.For this ...
ZHANG Limin,WANG Yanzhe,ZHANG Bingqiang,ZHU Nianbin
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