Combining NLP techniques and acoustic analysis for semantic focus detection in speech
András Beke, György Szaszák · 2014
Information extraction from written or spoken archives is a challenging infocommunication task, especially if a deep automatic analysis of the information structure is also targeted. The present research investigates focus detection approaching from an automatic analysis point of view for text (NLP) and speech (prosody) modalities. Deep syntactic analysis is performed with an NLP tool on speech transcripts and optionally combined with prosodic features extracted from speech to automatically detect the focus. Results show that in Hungarian, characterized by free word order and strong topic prominence, the detection of the focus based on NLP can be improved by adding prosodic features. Results also reflect however, that for the exploration of focus marking in speech, neither syntax nor prosody are sufficient: it is likely that semantic and pragmatic context also play an essential role in this process.