Descripción del proyecto
Desarrollo del sistema de generación de lenguaje natural del futuro
La generación de lenguaje natural (GLN) es un proceso de «software» que transforma automáticamente, a partir de datos estructurados y no estructurados, el lenguaje natural escrito o hablado en texto legible para el ser humano. En la actualidad, la GLN se enfrenta a algunos retos, como la controlabilidad semántica, la avaricia energética y la idoneidad para las lenguas con pocos recursos. El objetivo del proyecto M-FleNS, financiado por las Acciones Marie Skłodowska-Curie, es encontrar soluciones para algunos de los mayores retos de la GLN de última generación. En concreto, se investigará hasta qué punto es posible combinar los puntos fuertes de los sistemas neuronales y simbólicos, basados en la gramática, de GLN. El trabajo del proyecto conducirá al desarrollo de un nuevo tipo de sistema de GLN que aúna las técnicas simbólica y neuronal, lo que producirá mejores sistemas y componentes de GLN para aplicaciones de la vida real.
Objetivo
The core aim of the M-FleNS (Multilingual Flexible Neuro-Symbolic Language Generation) project is to explore the extent to which combining the strengths of neural and symbolic (grammar-based) Natural Language Generation (NLG) systems is possible. We will build FleNS generators that (i) exploit grammar-based system aspects to address the vexed problems of poor accuracy (including hallucinations and omissions of content) and data and energy-hungriness in neural generators, and (ii) exploit neural system aspects to address problems with fluency, coverage and robustness in grammar-based generators. The overall ambition is to find solutions for some of the biggest current challenges in state-of-the-art NLG, including semantic controllability, energy greed and suitability for low-resource languages. Combining the Applicant's expertise in symbolic NLG systems and data annotation with the Supervisor's expertise in machine learning and evaluation for NLG, and benefiting from the excellent ADAPT research environment, we will develop a new type of NLG system that combines the best of both worlds, symbolic and neural, to create better NLG systems and components for real-world applications.
The project is well aligned with the European Green Deal strategy and more particularly with the Digital Europe Programme whose main objectives include “bringing digital technology to businesses, citizens and public administrations”. Through a combination of working with the Supervisor and her research group, direct training, international collaboration and self-guided study, the Applicant will expand his spectrum of scientific expertise to Deep Learning methods and human evaluation of NLP systems, strengthen his general knowledge in linguistics, and acquire a comprehensive understanding of the IPR and business related skills needed for further exploitation. This project will allow the Applicant to establish himself as an internationally recognised research leader in the field of NLG.
Ámbito científico
Programa(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Régimen de financiación
HORIZON-AG-UN - HORIZON Unit GrantCoordinador
9 Dublin
Irlanda