Linguistic and multilingual issues in virtual worlds and serious games: a general review

Samuel Cruz-Lara, Alexandre Denis, Nadia Bellalem


Within a globalized world, the need for linguistic support is increasing every day. Linguistic information, and in particular multilingual textual information, plays a significant role for describing digital content: information describing pictures or video sequences, general information presented to the user graphically or via a text-to-speech processor, menus in interactive multimedia or TV, subtitles, dialogue prompts, or implicit data appearing on an image such as captions, or tags. It is obviously crucial to associate digital content to multilingual textual information in a non-intrusive way: the user must decide, whether or not, he wants to display the textual information related to the digital content he is dealing with in any particular language.

In this paper we will present a general review on linguistic and multilingual issues related to virtual worlds and serious games. The expression “linguistic and multilingual issues” will consider not only any kind of linguistic support (such as syntactic and semantic analysis) based on textual information, but also any kind of multilingual and monolingual topics (such as localization or automatic translation), and their association to virtual worlds and serious games. We will focus on our ongoing research activities, particularly in the framework of sentiment analysis and emotion detection. Note that we will also dedicate special attention to standardization issues because they grant interoperability, stability, and durability.

The review will essentially be based on our own experience but some interesting international research projects and applications will be also mentioned, in particular, research projects and applications related to sentiment analysis and emotion detection.


virtual worlds; serious games; linguistics; multilinguality; standardization; e-learning; language learning; natural language processing; sentiment analysis; emotion detection

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