Deep Collector
Automatically build a speaker dataset
How can I build up a dataset for my speaker recognition?
use case: Contextual Tagging
The challenge
At best, advertising should reach viewers when they are engaged with a particular topic. Intelligently aligned brand communication aims to reach potential buyers at the right time with an appropriate message. This is no different from cost-intensive advertising banners on television. It is therefore important to determine at which point an advertising message can be used most effectively. Individualization based on aired actions is an innovative way to optimize the playout timing of advertising media.
How can DeepVA help me place advertising when it fits thematically with the scene’s content played out on TV?
the solution
With the Deep Media Analyzer, you can use AI to capture the content shown in the respective broadcast scenes. With the help of Speech-To-Text, the spoken words of the protagonists can be converted into text files or packages and thus the subject can be analyzed. Relevant keywords such as “fresh”, “fruit” or “salad” are of particular relevance. Based on these keywords, a suitable advertising medium can now be simply selected. This is supported by the Deep Media Analyzer recognition functions such as Object, Face, and Landmark Recognition. They offer a comprehensive analysis of the scene shown and combined with speech recognition, can capture the content displayed quickly.
What results can be obtained?
Content-based ad placement through spoken word recognition
Contextual scene recognition through Recognition Services
Thematically targeted communication
faster data acquisition
COST REDUCTION
faster labelling
Equality and diversity insights
Often the spoken word alone is not enough: transcription is needed. Our Speech to Text function automates this process.
Face Recognition detects and identifies the faces of public figures in a variety of categories such as politics, sports, business, and entertainment.
Object and scene recognition detects and labels various objects and scenes, from general to more specific ones.
Landmark Recognition identifies all important sights, architectural structures and natural monuments across Europe. Easily archive and retrieve visual material showing places of interest for content creation.
Contact us
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Related use cases
How can I build up a dataset for my speaker recognition?
How can I recognize new speakers in my media assets in the future?
How can I efficiently find what I’m really looking for in my visual media material?
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A product of «The Chainless».
Designed and engineered in Germany.
The Chainless GmbH
Wannerstraße 19
79106 Freiburg
Germany
The project has indirectly received funding from the European Commission’s Horizon 2020 Framework Programme through the STADIEM project (Grant Agreement 957321)
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