Dr Félix do Carmo

Senior Lecturer in Translation and Natural Language Processing
BA, MA, PhD - University of Porto (Portugal)
+44 (0)1483 684118
09 LC 03
Office hours: Wednesdays & Fridays, from 11am to 12 noon.


Areas of specialism

Translation technologies; Post-editing of machine translation; Translation process research; Automatic post-editing; Applied translation studies; Natural language processing; Ethical and fair uses of technologies

My qualifications

BA in Modern Languages (ENG-PTG), professionalisation in Translation
University of Porto
MA in Translation Studies
University of Porto
PhD in Language Sciences
University of Porto


Research interests

Research projects


Postgraduate research supervision




Chapters in books

do Carmo, Félix, and Belinda Maia. 2015. Sleeping with the enemy? Or should translators work with Google Translate? in Pilar Sánchez-Gijón, Olga Torres-Hostench, Bartolomé Mesa-Lao (eds). Conducting Research in Translation Technologies. New Trends in Translation Studies. vol. 13. Peter Lang.

Articles in peer-reviewed journals


Conference proceedings

Shterionov, Dimitar, Félix do Carmo, and Joachim Wagner. 2019. “APE through Neural and Statistical MT with Augmented Data - ADAPT/DCU Submission to the WMT 2019 APE Shared Task.” In Proceedings of ACL 2019 - WMT Shared Task on Automatic Post-Editing. Firenze, Italy.

Shterionov, Dimitar, Félix do Carmo, Joss Moorkens, Eric Pacquin, Dag Schmidtke, Declan Groves, and Andy Way. 2019. “When Less Is More in Neural Quality Estimation of Machine Translation - an Industry Case.” In Proceedings of the MT Summit XVII. Dublin.

do Carmo, Félix. 2019 ‘Edit distances do not describe editing, but they can be useful for translation process research’, in Carl, M. and Hansen-Schirra, S. (eds) Proceedings of the 2nd MEMENTO workshop on Modelling Parameters of Cognitive Effort in Translation Production. Dublin, Ireland. pp. 1–2. (Abstract)

do Carmo, Félix. 2018. “Does Machine Translation Really Produce Translations?” In Proceedings of the 21st Annual Conference of the European Association for Machine Translation - Translator’s Track, edited by Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Miquel Esplà-Gomis, Maja Popović, Célia Rico Pérez, André Martins, Joachim Van den Bogaert, and Mikel L. Forcada, 323. Alicante, Spain: EAMT. p. 323. (Abstract).

do Carmo, Félix, Luís Trigo, and Belinda Maia. 2016. From CATs to KATs. in Proceedings of the 38th Conference Translating and the Computer. London, UK: Editions Tradulex, Geneva. pp. 149–158.

do Carmo, Félix, and Belinda Maia. 2016. “A Description of Post-Editing, from Translation Studies to Machine Learning.” In Tradumàtica Research Group (eds.). Translators and Machine Translation: Book of presentations. Barcelona, Spain. pp. 126-152.

Shenbin Qian, Constantin Orasan, Diptesh Kanojia, Hadeel Saadany, Felix do Carmo (2022)SURREY-CTS-NLP at WASSA2022:An Experiment of Discourse and Sentiment Analysis for the Prediction of Empathy, Distress and Emotion, In: PROCEEDINGS OF THE 12TH WORKSHOP ON COMPUTATIONAL APPROACHES TO SUBJECTIVITY, SENTIMENT & SOCIAL MEDIA ANALYSISpp. 271-275 Assoc Computational Linguistics-Acl

This paper summarises the submissions our team, SURREY-CTS-NLP has made for the WASSA 2022 Shared Task for the prediction of empathy, distress and emotion. In this work, we tested different learning strategies, like ensemble learning and multi-task learning, as well as several large language models, but our primary focus was on analysing and extracting emotion-intensive features from both the essays in the training data and the news articles, to better predict empathy and distress scores from the perspective of discourse and sentiment analysis. We propose several text feature extraction schemes to compensate the small size of training examples for fine-tuning pretrained language models, including methods based on Rhetorical Structure Theory (RST) parsing, cosine similarity and sentiment score. Our best submissions achieve an average Pearson correlation score of 0.518 for the empathy prediction task and an F1 score of 0.571 for the emotion prediction task(1), indicating that using these schemes to extract emotion-intensive information can help improve model performance.

Sarah Herbert, Félix do Carmo, Joanna Gough Results from project JAS (Job Allocation System) University of Surrey

This dataset includes the data collected as part of the projects JAS, a study on the effects of automation of a job allocation system in a translation services company. The dataset includes counts of answers to a questionnaire answered by 38 participants. Answers are classified according to closed classes in closed questions, and thematic codes in answers to open questions. See readme file for more details and read the article "From responsibilities to responsibility: a study of the effects of translation workflow automation", due to be published in JoSTrans, Issue 40 (July 2023).

The amazing capacities of machine translation are supported by very rigorous and powerful research. However, science is also discourse, and sometimes scientific discourse creates myths, beliefs that are based on how terms and concepts may be used in scientific publications with no proper debate or understanding. In this lecture, I will present a critical view of three of the most influential papers from machine translation research, not criticising their scientific validity, but highlighting how their use of terms and concepts helped create myths around the power of machine translation. My perspective is that translation is much more complex than what common discourses about machine translation convey, and that we are losing sight of that complexity when we focus on the scientific achievements. My objective is to contribute to real convergence between machine translation research and translation studies by presenting a view that aims at solving current limitations of discussions about translation. I believe that real convergence can only be fruitful if translation studies contributes to the debate, bringing with it the power of a rich legacy of theories and practices that help us all understand the complexity of translation.

Additional publications