openSmile_book

We start introducing openSMILE by addressing two important questions for users who are new to openSMILE : What is openSMILE ? and Who needs openSMILE ?. If you want to start using openSMILE right away, then you should start reading section 2, or section 2.3 if you have already managed to install openSMILE.

Emotion Recognition System for the Multimodal Emotion Challenge

This paper presents the University of Passau s approaches for the Multimodal Emotion Recognition Challenge 2016.

基于音频的多模态二分类情感识别

Video-based Emotion Recognition Using Multi-dichotomy RNN-DNN

The Multimodal Emotion Recognition Challenge of CCPR 2016

Emotion recognition is a significant research filed of pattern recognition and artificial intelligence. The Multimodal Emotion Recognition Challenge(MEC) is a part of the 2016 Chinese Conference on Pattern Recognition (CCPR).The goal of this competition is to compare multimedia processing and machine learning methods for multimodal emotion recognition. The challenge also aims to provide a common benchmark data set, to bring together the audio and video emotion recognition communities, and to promote the research in multimodal emotion recognition. The data used in this challenge is the Chinese Natural AudioVisual Emotion Database (CHEAVD), which is selected from Chinese movies and TV programs. The discrete emotion labels are annotated by four experienced assistants. Three sub-challenges are defined: audio, video and multimodal emotion recognition. This paper introduces the baseline audio, visual features,and the recognition results by Random Forests

tensorflow

TensorFlow™ 是一个开放源代码软件库，用于进行高性能数值计算。借助其灵活的架构，用户可以轻松地将计算工作部署到多种平台（CPU、GPU、TPU）和设备（桌面设备、服务器集群、移动设备、边缘设备等）。TensorFlow™ 最初是由 Google Brain 团队（隶属于 Google 的 AI 部门）中的研究人员和工程师开发的，可为机器学习和深度学习提供强力支持，并且其灵活的数值计算核心广泛应用于许多其他科学领域。