Special Session on Advanced AI-based Data Annotation Tools (AI-DAT)


The past, present and future of artificial intelligence (AI) is closely linked to the efficient preparation and quality of data, which directly influences the performance of algorithms such as artificial neural networks. The allocation of resources to data annotation currently represents approximately 80% of investments in AI-based solutions, highlighting the strategic importance of research into advanced data annotation tools and their alignment with industry trends. Research on advanced data annotation tools is essential to improve the efficiency and quality of the data preparation process, as well as to address everyday technological challenges related to diverse information sources. 

The session is proposed by SIGMA Cognition and the Applied Artificial Intelligence Group (GIAA) from Universidad Carlos III de Madrid. SIGMA, as a company specialized in data annotation services, recognizes the strategic importance of this task. Through its SIGMA.AI and SIGMA Cognition units and the collaboration with GIAA, SIGMA plays a key role in the development of artificial intelligence-based data annotation tools. The special session "Research on advanced AI-Based data Annotation Tools" as a result of the SIGMA Cognition project HADA (Herramientas de Anotación de Datos Avanzadas) center in the research of AI techniques in annotation tools search for new developments in this area. This session aims to share and discuss new research on AI tools and algorithms in a data annotation framework, with the goal of creating advanced tools that optimize the collection of high-quality data more efficiently and accurately than existing tools. The session will also include the participation of the Signal Processing Applications Group (GAPS) of the Polytechnic University of Madrid, which has closely collaborated with Sigma in the research and development of audio annotation processes. 


Some of the topics included in this session but not limited are:

  • Human-in-the-loop Artificial Intelligence (HITL-AI)
  • Image and video segmentation
  • Audio Processing
  • Sound Event Detection
  • Speech Anotation
  • Automated audio, text, image and video annotation
  • Pre-anotation processes in text, image and video (Data preparation / curation)
  • Generative AI and Synthetic Data

Organizing Committee

  • Juan Pedro Llerena (Universidad de Alcalá)
  • Miguel Ángel Patricio (Universidad Carlos III de Madrid)
  • Ester Sancho (SIGMA Cognition)
  • Silvia Rodríguez-Jiménez (SIGMA Cognition)

Program Committee

  • Jorge Rico (Head of NLP and NLU Technologies at Sigma Cognition)
  • Silvia Rodríguez-Jiménez (Computer Vision Director at Sigma Cognition)
  • Juan Manuel Perero (Head of Speech Technologies at Sigma Technologies Global)
  • Angel Mora (Research Scientist, Computer Vision at Sigma Cognition)
  • Jaime Corton (Computer Vision Engineer at Sigma Cognition)
  • Fernando Espinoza (Research Scientist, Speech processing at Sigma Cognition)
  • Jose Manuel Molina Lopez (Ph.D. in telecommunications engineering from the UPM, professor in the area of Computer Science and Artificial Intelligence at the Carlos III University of Madrid and director of the GIAA group)
  • Miguel Ángel Patricio Guisado (PhD in Computer Science from the Universidad Politécnica de Madrid, and is a professor in the area of Computer Science and Artificial Intelligence at the Universidad Politécnica de Madrid)
  • Luis Hernández Gómez (University Professor ETSI of Telecommunications UPM)
  • Ramón Fernandez Castañon (Masters student at UPM)