GoViz
Public speech from government figures often describes relevant actions that can impact the population’s lives. However, most people do not have time and access to analyze and understand public speech. Such a scenario narrows the participation of the people in the main discussions, which leads to multiple misunderstandings. In this work, we propose GoViz, a tool that automatically produces visual representations to outline governmental speeches regarding the subject, its main actors, and how they connect to the discussion topics. GoViz processes natural language from speech transcriptions in a pipeline that identifies part-of-speech elements, named-entities, and the relation between persons, making speech content more accessible and insightful. Using publicly available data, we evaluate our tool in two different languages (Portuguese and English). The results demonstrate that the visualizations from both data facilitate understanding the speech content. Thus, our main contribution is to encourage the participation of citizens in parliamentary issues, allowing a simplified and visually engaging avenue to access long speeches and fostering improved communication between parliamentarians and the population.
Authors
- Isabel Harb Manssour (ORCID: https://orcid.org/0000-0001-9446-6757)
- João Paulo Aires (ORCID: https://orcid.org/0000-0001-6947-5766)
- Dalvan Griebler (ORCID: https://orcid.org/0000-0002-4690-3964)
- Larissa Guder
Institutions
- Pontifícia Universidade Católica do Rio Grande do Sul (BR)
Publication Details
- Journal
- Conference on Digital Government Research
- Published
- 2025-05-19
- DOI
- https://doi.org/10.59490/dgo.2025.954
- Primary Topic
- Multimodal Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul