Results 41 to 50 of about 545,669 (204)
Environmental Sound Recognition Using Time-Frequency Intersection Patterns
Applied Computational Intelligence and Soft Computing, 2012 Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we use a multistage perceptron neural network system for environmental sound recognition.
Xuan Guo +5 more
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Signal Classification in Quotient Spaces via Globally Optimal Variational Calculus
, 2017 A ubiquitous problem in pattern recognition is that of matching an observed time-evolving pattern (or signal) to a gold standard in order to recognize or characterize the meaning of a dynamic phenomenon.
Chirikjian, Gregory S
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Integrated Inference and Learning of Neural Factors in Structural Support Vector Machines [PDF]
, 2016 Tackling pattern recognition problems in areas such as computer vision, bioinformatics, speech or text recognition is often done best by taking into account task-specific statistical relations between output variables.
De Turck, Filip, Houthooft, Rein
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The Pattern Recognition Methods for Emotion Recognition with Speech Signal [PDF]
Journal of Control, Automation and Systems Engineering, 2006 In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features.
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Research on Speech Emotion Recognition Method Based A-CapsNet
Applied Sciences, 2022 Speech emotion recognition is a crucial work direction in speech recognition. To increase the performance of speech emotion detection, researchers have worked relentlessly to improve data augmentation, feature extraction, and pattern formation.
Yingmei Qi, Heming Huang, Huiyun Zhang
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Statistical pattern recognition approach to speech segmentation [PDF]
The Journal of the Acoustical Society of America, 1974 It is believed by many speech researchers that there is abundant information contained in the transition segments [J. L. Flanagan, Speech Analysis, Synthesis and Perception (1972), 2nd ed.]. This paper describes an algorithm to recognize different segments of connected speech, e.g., voiced, unvoiced, silence, and transition.
K. Ganesan, Wen C. Lin
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Speech signal analysis and pattern recognition in diagnosis of dysarthria
Annals of Indian Academy of Neurology, 2017 Background: Dysarthria refers to a group of disorders resulting from disturbances in muscular control over the speech mechanism due to damage of central or peripheral nervous system.
Minu George Thoppil +3 more
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Attention-based Wav2Text with Feature Transfer Learning
, 2017 Conventional automatic speech recognition (ASR) typically performs multi-level pattern recognition tasks that map the acoustic speech waveform into a hierarchy of speech units.
Nakamura, Satoshi +2 more
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Speech Pattern Based Black-Box Model Watermarking for Automatic Speech Recognition
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 5 pages, 2 figures. Acceptted by 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Chen, Haozhe +5 more
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Entropy, 2022 In this article, the concept (i.e., the mathematical model and methods) of computational phonetic analysis of speech with an analytical description of the phenomenon of phonetic fusion is proposed.
Viacheslav Kovtun +2 more
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