We present a system to support simultaneous interpreting in specific domains. The system is going to be developed through a strong synergy among technicians, mostly experts on both speech and text processing, and end-users, i.e. professional interpreters who define the requirements and will test the final product. Some preliminary encouraging results have been achieved on benchmark tests collected with the aim of measuring the performance of single components of the whole system, namely: automatic speech recognition (ASR) and named entity recognition.

In this paper, we describe a new web-based corpus for hypernym detection. It consists of 32 GB of high quality english paragraphs along with their part-of-speech tagged and dependency parsed versions. For hypernym detection, the current state-of-the-art uses a corpus which is not available freely. We evaluate the state-of-the-art methods on our corpus and achieve similar results. The advantage of this corpora is that it is available under an open license. Our main contribution is the corpus with POS-tags and dependency tags and the code to extract and simulate the results we have achieved using our corpus.