Video , Audio and Speech feature

 

 

paper: Joint Audio-Visual Bi-Modal Codewords for Video Event Detection.  Guangnan Ye, I-Hong Jhuo, Dong Liu, Yu-Gang Jiang, D.T. Lee, Shih-Fu Chang  In ACM International Conference on Multimedia Retrieval (ICMR)   Hong Kong   June, 2012

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A Hybrid Content- and Concept-Based Approach to Large-Scale Video Analytics

Figure 1. Architecture based on a hierarchical deep neural network (H-DNN) and hidden Markov models (HMMS) for audio-only video event detection. MFCCS (mel-frequency cepstral coefficients) are commonly used in speech recognition systems, and MLP (multilayer perceptron) is an artificial neural network that maps sets of input data onto a set of appropriate outputs.
Figure 2. Processing chain for deep neural-network audio-only video event detection (top). The deep neural-network architecture comparison is shown lower left. Deep neural-network sampling and training efficiency comparison is shown lower right.

Best links

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Ref: https://openbook4.me/projects/238/sections/1557

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Paper :Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks

 

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Wake-Up-Word Speech RecognitionRelated image

Speech Processing Laboratory – CTU

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Video editing based on behaviors-for-attention – a

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==========================================================================https://steveblank.com/tools-and-blogs-for-entrepreneurs/

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Deep learning for computational biology

http://msb.embopress.org/content/12/7/878

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Video Applications

Ref : https://handong1587.github.io/deep_learning/2015/10/09/video-applications.html

Real-time Action Recognition with Enhanced Motion Vector CNNs

 

Video Understanding

 

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