MixedEmotions = Big Linked Data Platform for Emotional Analysis

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Today, emotion detection services based on speech technologies make its way to the market. Speech bears valuable information about speakers; and emotions of the speaker are one of them. Just try to imagine the potential power you can get, if you have a mining tool for emotions.

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Emotion Detection from Speech – Thesis successfully defended

 

The Bachelor Thesis deals with research in the field of emotion recognition mainly from speech and marginally from other modalities (video and physiological data).

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Meet us @LDK 2017

ldk-2017-ireland

LDK is the new biennial conference series on Language, Data and Knowledge. The conference aims at bringing together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications.

Paul Buitelaar, coordinator the from MixedEmotions project will be present.

Meet us there and follow us on Twitter @mixed_eu or @unlp_insight

MixedEmotions sponsors LDK.

 

The MixedEmotions platform is a Big Data Toolbox for multilingual and multimodal emotion analysis

It is built around stand alone docker modules with an orchestrator that links the modules into analysis workflows utilising MESOS for scalable cloud deployment.

Tuesday March 28, 2017, 4pm CET –REGISTER NOW.

Core capabilities include emotion extraction from text, audio and video with many other capabilities, such as sentiment analysis, social network analysis, entity detection and linking and sophisticated data visualisation.

You want more info? Download the handouts:

 

Take me to the MixedEmotion’s Platform.
Take me to the MixedEmotion’s Github Account and Docker Account and read our DIY – Emotion Extraction Platform Made Easy article.

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MixedEmotions – the Open Source platform* for emotion extraction

The MixedEmotions platform is a Big Data Toolbox for multilingual and multimodal emotion extraction and analysis (*be aware the plattform is in a beta stadium and still under development). It can extract emotions from text, audio and video. However, it also has many other capabilities, such as sentiment analysis, social network analysis and knowledge graphs visualization among others. Bring me directly to the platform on Docker.

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Joining the world of emotions with media consumption. This is what MixedEmotion’s Social TV pilot aims at.

The following article illustrates our starting point. It shows the achievements that were made one year into the two-year project.

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Gestures, mimics, and speech are the key ways to communicate and convey thoughts to others. However, the content of speech (e.g., words) only serves around seven percent of communications. The other parts of human communication include HOW we talk (38%) and how we move our body and perform facial mimics (55%) [1].
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The project MixedEmotions proposes to follow a linked data approach for publishing emotions. What does this mean?

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Emotions are an integral aspect of human mental processes and everyday experience. They drive much of our behaviour and play an important part in communication. Emotions are often intertwined with mood, temperament, personality, disposition, and motivation.

To understand human emotions, to react to them, and to intentionally induce them has been a long-standing dream of researchers in human-computer interaction. How much better could our lives be if computers, search engines, or smart personal assistants would be able to sense when we start getting annoyed or frustrated with them and if they could adapt accordingly?

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