By Florian Eyben
This ebook reviews on a great thesis that has considerably complex the cutting-edge within the automatic research and class of speech and tune. It defines numerous normal acoustic parameter units and describes their implementation in a singular, open-source, audio research framework known as openSMILE, which has been authorised and intensively used around the world. The booklet bargains broad descriptions of key equipment for the automated category of speech and song indications in real-life stipulations and studies at the evaluate of the framework constructed and the acoustic parameter units that have been chosen. it's not basically meant as a guide for openSMILE clients, but additionally and essentially as a advisor and resource of notion for college kids and scientists excited about the layout of speech and song research equipment that may robustly deal with real-life conditions.
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Additional info for Real-time Speech and Music Classification by Large Audio Feature Space Extraction
2013b) . . . . . . . . . Area under (ROC) curve (AUC) frame-level results on the synthetic validation and test sets of LSTM-RNN approaches Net1 and Net2 and the RAM05, ARG, and ..... 81 125 ..... 125 ..... 127 ..... 128 ..... 129 ..... 131 134 ..... 134 ..... 168 ..... 11 List of Tables SOHN reference algorithms as reported in (Eyben et al. 2013b). . . . . . . . . . . . . . . . . Frame-level results for the DVD film test set of nets Net1 and Net2 and the SOHN algorithm .
Dimensional affect ratings’ statistics for the evaluation (test) set of the SEMAINE database as used in this thesis . . . . . . . . . . . . . . . . . (Pearson) Correlation Coefficient (CC) between all labellers for each of the five dimensions, computed from the evaluation set sessions . . . . . . . . Pairwise (Pearson) Correlation Coefficient (CC) between all five dimensions, computed on the evaluation set sessions . . . . . . . . . . . . . . . Overview of the 11 chosen speech/singing emotion databases; corpora 9–11 shown here (GeSiE, SUSAS, VAM) .
1–4 July, 2013a F. Eyben, F. Weninger, L. Paletta, B. Schuller, The acoustics of eye contact—Detecting visual attention from conversational audio cues. In Proceedings of the 6th Workshop on Eye Gaze in Intelligent Human Machine Interaction: Gaze in Multimodal Interaction (GazeIn ’13), held in conjunction with the 15th International Conference on Multimodal Interaction (ICMI) 2013, ACM. Sydney, Australia, pp. 7–12, December 2013b M. Fingerhut, Music information retrieval, or how to search for (and maybe find) music and do away with incipits.
Real-time Speech and Music Classification by Large Audio Feature Space Extraction by Florian Eyben