Media content deep learning

When a national broadcaster came to our labs, its questions were:

What types of content engage the more with consumers?
When does a customer feel close to a story?
Which is the best media content that increases attention?

BMU Labs provided a complete solutions to find the answers. The result is a better understanding of content consumption and a relevant improvement of podcast and short video web content.

Our team suggested to use different assets such as:
– Module presenting an emotional analysis of an individual listening or watching media content
– Module presenting an emotional journey of an individual through different sequences
– Module for predicting future emotions of an individual in prevision for the next sequences

BMU Labs - Neural Manager

BMU Labs Neuro express has been used for this analyzis. This solution apply machine
learning (ML) algorithms on raw brain electrical signal to determine facial expressions from
the brain electrical signal.

BMU Labs- Facial expression EEG

Emotions analyzis relied on the Russell’s circumplex model and ML algorithms on brain data,
we could map the emotions felt by an individual and follow his emotional trail. And to complete our work, BMU labs deployed, with the use of the EEG to collect brain electrical signal and brainwaves, a solution to monitor mental states such as:
?Stress (short & long terms)
?Frustration
?Excitement
?Meditation
?Etc.

Media content deep learning

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