Mental, neurological and/or physical disabilities often affect individuals’ cognitive processes, which in turn can introduce difficulties with remembering what they have learnt. Therefore, completing trivial daily tasks can be challenging and supervision or help from others is constantly needed. In this regard, these individuals with special needs can benefit from nowadays advanced assistance techniques. Within this contribution, a language-driven, workplace integrated, assistance system is being proposed, supporting disabled individuals in the handling of certain activities while taking into account their emotional-cognitive constitution and state. In this context, we present a set of baseline results for emotion recognition tasks and conduct machine learning experiments to benchmark the performance of an automatic emotion recognition system on the collected data. We show that this is a challenging task that can nevertheless be tackled with state-of-the-art methodologies.