@InProceedings{Höbel-Müller2019_77,
author = {Juliane Höbel-Müller and Ingo Siegert and Ralph Heinemann and Alicia Flores Requardt and Michael Tornow and Andreas Wendemuth},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2019},
title = {Analysis of the influence of different room acoustics on acoustic emotion features},
year = {2019},
editor = {Peter Birkholz and Simon Stone},
month = mar,
pages = {156--163},
publisher = {TUDpress, Dresden},
abstract = {In automatic analyses of speech and emotion recognition, it has to beensured that training and test conditions are similar. The presented study aims toinvestigate the influence of certain room acoustics on common features used foremotion recognition. As a benchmark database this study focuses on the BerlinDatabase of Emotional Speech. The following rooms were analysed: a) modernlecture hall, b) older lecture hall, and c) staircase. For all rooms and their differentrecording setups, different acoustic measures were captured. The speech record-ings analysed in this paper were realized only at the ideal locations within therooms. Afterwards, 52 features (LLDs of emobase) were automatically extractedusing OpenSMILE and a sample-wise statistical analysis (pairedt-test) was carriedout. Therefore, the number of acoustically degraded features and its effect sizecan be linked to the acoustic parameters of the different recording experiments. Asresult, 15% of the degraded samples show a highly significant difference regard-ing all considered rooms. Especially MFCCs account for approximate 50% of thedegradation. Furthermore, the degradation is analysed depending on the emotionand room acoustic.},
isbn = {978-3-959081-57-3},
issn = {0940-6832},
keywords = {Poster und Demonstrationen},
url = {https://www.essv.de/pdf/2019_156_163.pdf},
}