Development of machine learning systems

Abstract

Machine learning is a branch of artificial intelligence that deals with the development of theory and algorithms to build systems capable of learning from data.

The MLLP group’s research covers different approaches to machine learning, such as supervised, semi-supervised, unsupervised, adaptive and deep learning. Special interest is devoted to the development of accurate and efficient machine learning algorithms applicable to real-life problems.

Machine learning techniques are applicable to a wide range of classification problems where the objective is to categorize objects among a set of categories.

MLLP research focuses on the development of machine learning systems based on several complementary technologies, such as automatic speech recognition, speech synthesis and statistical machine translation.

The MLLP group develops systems based on machine learning techniques to be used in real life applications. Particularly in applications related to multilingual communication and large-scale data processing. The developed systems are specifically tailored to the application improving its performance and human-machine interaction.

These systems are distributed publicly under open source licenses. The performance of the open source tools developed by the MLLP group can be optimized by contracting consulting services to all interested customers.

The members of the MLLP group have acquired extensive experience in the development of machine learning based applications through their participation in numerous national and international research projects financed with public and private funds.

Scientific officer

Juan Císcar Alfonso

Stakeholders

Applications

  • Automatic speech recognition
  • Speech synthesis
  • Statistical machine translation
  • Multilingual communication
  • Large-scale data processing

Technical advantages

  • Improved human-machine interaction

Benefits it provides

  • Performance improvement