This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). Without any structure, a film is just a collection of a few thousand frames of images…

This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). The Moviegoer prototype is complete, the unveiling includes a technical demonstration as well as two background…

Movies demonstrate emotional communication atop valuable societal context. They are the perfect dataset for emotional AI models. — Smart devices, digital assistants, and service chatbots are becoming ubiquitous, but they don’t yet have the emotional capacity they need to fully understand how we communicate. Emotional AI models should be able to detect specific emotions and act with empathy, understand societal norms, and recognize specific communicational nuances, like irony…

Film is the key to teaching emotion to AI. As I argued in a previous post, machines will learn emotions by “watching” movies. By turning cinema into structured data, we can unlock a trove of emotional data which can then be used to train AI models. Moviegoer is a tool…

In the near-future, we’ll be surrounded by AI entities who act just like humans. They’ll be able to maintain conversations with the perfect amount of hesitations, slang, and cadence to be indistinguishable from a person. They’ll be able to interact with us and know exactly how we’re feeling, analyzing our…

This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). With scenes and their details identified, we turn our attention to characters. Tracking characters (along with…

This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). We’ve improved our scene-boundary detection algorithm, and we’ve been able to detect two-character dialogue scenes throughout…

This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). We’ve just begun to use all the clues we learn from a film’s visuals, audio, and…

This is part of a series describing the development of Moviegoer, a multi-disciplinary data science project with the lofty goal of teaching machines how to “watch” movies and interpret emotion and antecedents (behavioral cause/effect). Now that we’re starting to use features from the visual, audio, and subtitle tracks together, we…