DescriptionThe International Conference on Computational Processing of Portuguese (PROPOR) is the main event in the area of human language processing that is focused on theoretical and technological issues of written and spoken Portuguese and Galician. The meeting has been a very rich forum for the exchange of ideas and partnerships for the research and industry communities dedicated to the automated processing of Portuguese, promoting the development of methodologies, resources and projects that can be shared among researchers and practitioners in the field.
This year edition calls for papers describing work on any topic related to computational language and speech processing of Portuguese by researchers in the industry or academia. Topics of interest include:
- Human speech production, perception and communication
- NLP-oriented linguistic description or theoretical analysis
- Natural language processing tasks (e.g. parsing, word sense disambiguation, coreference resolution)
- Natural language processing applications (e.g. question answering, subtitling, summarization, sentiment analysis)
- Speech technologies (e.g. spoken language generation, speech and speaker recognition, spoken language understanding)
- Speech applications (e.g. spoken language interfaces, dialogue systems, speech-to-speech translation)
- Resources, standardization and evaluation (e.g. corpora, ontologies, lexicons, grammars)
- Language and speech processing in academic disciplines
- Portuguese language variants and dialect processing (including the language varieties of Angola, Brazil, Cape Verde, East Timor, Galicia, Guinea-Bissau, Macao, Mozambique, Portugal, and Sao Tome and Principe)
- Multilingual studies, methods, applications and resources including Portuguese.
PROPOR will have for the first time two tracks dedicated to Linguistics and Resources and to Industry, apart from the traditional NLP research track (named "General").
|Period||2021 → 2022|
|Degree of Recognition||International|
- Computational Linguistics
- NLP-oriented linguistic