The development of technologies for the automatic analysis and annotation of audiovisual data requires a solid understanding of signal processing and machine learning, along with a good comprehension of the underlying requirements.
Another challenge lies in multimodal analysis and orchestration: extracting metadata from audio, video, and image files involves a variety of processes ranging from preprocessing to feature extraction and classification. Different methods and technologies are employed, requiring flexible integration and orchestration. The integration of heterogeneous data from different sources and formats also requires the selection or development of suitable data models and metadata standards. Media archives often deal with large volumes of data, imposing specific requirements on system architecture, efficiency, and the optimization of the algorithms used.
Furthermore, we are involved in metadata standards, as well as the integration and orchestration of analysis components. We also address privacy concerns and other aspects of trustworthy AI, aiming to provide comprehensive solutions for specific application requirements.