# Text-Based Emotion Recognition in English and Polish for Therapeutic Chatbot
## 7 Conclusions  
In this article, we presented the results of our experiments on sentiment polarity and emotion recognition for English and Polish texts, aiming to work in the context of a therapeutic chatbot. We extended the existing language resources by adding samples of neutral texts to an existing English corpus. Next, we created a Polish version of the English database using neural machine translation. We used the corpus created in this way, which we named CORTEX, for experiments on sentiment and emotion classification. To show statistical significance, we calculated the [PERSON] score interval for each evaluation metric.  
The results obtained were satisfactory: the best scores were achieved for the BERT-based classifiers, where accuracy of over 90% was achieved for sentiment (3-class) classification and almost 80% for emotion (9-class) classification. The results for Polish always turned out inferior to those for English, which might be caused either by imperfections in the MT process, or by the nature of the Polish language itself, as it is characterized by a more complex grammar and morphology. Exact research on this topic will be the subject of future work.  
Our novel contributions presented in this article are as follows:  
* From existing resources, we created a new dataset containing empathetic utterances in English, which were annotated with nine emotion classes, including neutral texts.
* Using neural machine translation, we created a Polish version of the above database, thus filling a gap in text resources for the Polish language. The two language versions of the database formed a new parallel corpus, named CORTEX.
* We ran a series of experiments with sentiment polarity and emotion classification, establishing that the BERT-based classifier is currently the best method. Thus, we set a baseline for potential future researchers.
* We showed the difference in classification efficacy for English and Polish and discussed possible explanations for this.  
We made CORTEX, the developed dataset, available to the research community at [[https://github.com/azygadlo/CORTEX](https://github.com/azygadlo/CORTEX)]([https://github.com/azygadlo/CORTEX](https://github.com/azygadlo/CORTEX)), accessed on 21 May 2021 and encourage researchers to use it for future experiments. We believe that this will help in designing better, more empathetic chatbots and dialogue systems, both for English and Polish. We also strongly encourage the creation of new versions of our database by extending it with next language versions.  
Conceptualization, A.Z., M.K. and A.J.; methodology, A.Z., M.K. and A.J.; software, A.Z.; validation, A.Z.; investigation, A.Z., M.K. and A.J.; data curation, A.Z.; writing--original draft preparation, A.Z., M.K. and A.J.; writing--review and editing, A.Z., M.K. and A.J.; visualization, A.Z.; supervision, A.J.; project administration, A.J.; funding acquisition, A.Z., M.K. and A.J. All authors have read and agreed to the published version of the manuscript.  
**Funding:** Research was funded by the Center for Priority Research Area Artificial Intelligence and Robotics of the Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) program.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** CORTEX is freely available at [[https://github.com/azygadlo/CORTEX](https://github.com/azygadlo/CORTEX)]([https://github.com/azygadlo/CORTEX](https://github.com/azygadlo/CORTEX)), accessed on 21 May 2021.  
**Conflicts of Interest:** The authors declare no conflict of interest.