Results 31 to 40 of about 938 (162)
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
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Attention-Enhanced Connectionist Temporal Classification for Discrete Speech Emotion Recognition [PDF]
Interspeech 2019, 2019 Discrete speech emotion recognition (SER), the assignment of a single emotion label to an entire speech utterance, is typically performed as a sequence-to-label task. This approach, however, is limited, in that it can result in models that do not capture temporal changes in the speech signal, including those indicative of a particular emotion.
Ziping Zhao 0001 +5 more
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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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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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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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IEEE Access, 2018 The end-to-end learning approaches were proposed for an arithmetic expression recognition task in the Baidu Meizu Deep Learning Competition by a deep convolutional neural network (DCNN) with parallel dense layers and component-connection-based detection ...
Yuxiang Jiang +2 more
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CNN-RNN BASED HANDWRITTEN TEXT RECOGNITION
ICTACT Journal on Soft Computing, 2021 At present most of the scripts are handwritten due to the ease of using a pen tip in place of a keyboard, hence errors are common due to illegibility of the human handwriting. To avoid this problem handwriting recognition is essential.
Hemanth G R +4 more
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IEEE Access, 2022 To solve the problem of the low recognition rate of continuous dynamic gestures in Chinese sign language, a non-invasive end-to-end continuous dynamic gesture recognition system combining Inertial Measurement Unit (IMU) signal and surface ...
Jinquan Li +3 more
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Towards end-to-end speech recognition with transfer learning
EURASIP Journal on Audio, Speech, and Music Processing, 2018 A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training with matrix factorization algorithm is ...
Chu-Xiong Qin, Dan Qu, Lian-Hai Zhang
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Applied Sciences, 2021 State-of-the-art Optical Music Recognition (OMR) techniques follow an end-to-end or holistic approach, i.e., a sole stage for completely processing a single-staff section image and for retrieving the symbols that appear therein.
María Alfaro-Contreras +1 more
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