The MixedEmotions platform is a Big Data Toolbox for multilingual and multimodal emotion extraction and analysis. 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.
Take me directly to The MixedEmotion’s platform.
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.
The Bachelor Thesis deals with research in the field of emotion recognition mainly from speech and marginally from other modalities (video and physiological data).
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.
MixedEmotions sponsors LDK.
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. Take me directly to the MixedEmotion’s Platform.
Interactive Business Webinar about the MixedEmotions Platform
When is the next webinar? We are happy to welcome you at June 30th at 12h CEST. Just access http://joingotomeeting.com, and enter meeting id 248-510-485
MixedEmotions brings emotion analysis to your business. We are developing an open source platform for the automatic detection of emotions in speech, audio, video, text and social media data – in multiple languages and with preservation of the semantic context of expressed emotions.
Can you imagine your alarm clock knew if you slept badly and chose your favorite song to raise your spirits? Or that your TV chose for you that movie you needed today to make you smile? Or that your car suggests you to stop to grab a cup of coffee?
These premises, which until now were part of science fiction cinema, from classics like Blade Runner to more current hits like Her, may be closer to reality. Thanks to the convergence of technologies of analysis of emotions, Big Data, and Internet of Things (IoT). Both are being researched in the European project MixedEmotions.