Emotion-aware movie characterization with Oliver API

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Content-based Movie Recommendation Systems

Content-based indexing methods have been helping us manage the huge amounts of multimedia data available online, by utilizing intelligent content search and recommendation. A popular application in that context is movie recommendation systems, which are based on

  • movie attributes that are statistically mapped to the user preferences (content-based systems) or
  • both (hybrid systems)

What about emotions in movies?

So multimodal information can be used to extract information in movies that can make the recommendation process more “insightful” as it will also take into account what we see and listen to when watching a movie. But what about the underlying emotions of movies? It is obvious that the emotions that are expressed by the actors can also play an important role in discovering a high-level content representation that will make the recommendation and search process richer. In other words, the negative, positive, strong and weak emotions that appear in a movie can influence our movie preferences.

Extract emotions from speech using Oliver API

Oliver is Behavioral Signal’s Emotion Artificial Intelligence (#EmotionAI) API. Developers can directly benefit from Oliver’s growing emotional intelligence, measure emotions and behaviors in conversations, and utilize our continuously evolving robust analytics in their own applications. Either that involves development of a virtual assistant (VA) for a business, an interactive game for children, a voice-controlled speaker for the home, or a social robot designated to assist the elderly, incorporating emotion-aware spoken language understanding will supercharge your users’ experience. One can use Oliver to send audio or video data and retrieve automatically generated behavioral annotations in JSON format.

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Behavioral Signals - Emotion AI

Building the fastest evolving robust emotionAI engine

Theodore Giannakopoulos

Written by

PhD in audio signal analysis and machine learning. Over 10 years in academia. Currently Director of Machine Learning at Behavioral Signals.

Behavioral Signals - Emotion AI

Building the fastest evolving robust emotionAI engine

Theodore Giannakopoulos

Written by

PhD in audio signal analysis and machine learning. Over 10 years in academia. Currently Director of Machine Learning at Behavioral Signals.

Behavioral Signals - Emotion AI

Building the fastest evolving robust emotionAI engine

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