| 书目名称 | Real-time Speech and Music Classification by LargeAudio Feature Space Extraction |
| 编辑 | Florian Eyben |
| 视频video | |
| 概述 | Nominated as an outstanding thesis.by Technische Universität München, Germany.Describes the details and.architecture of openSMILE - the number 1 open-source toolkit in speech emotion.analytics and com |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | .This book reports on an outstanding thesis thathas significantly advanced the state-of-the-art in the automated analysis andclassification of speech and music. Itdefines several standard acoustic parameter sets and describes theirimplementation in a novel, open-source, audio analysis framework calledopenSMILE, which has been accepted and intensively used worldwide. The bookoffers extensive descriptions of key methods for the automatic classificationof speech and music signals in real-life conditions and reports on theevaluation of the framework developed and the acoustic parameter sets that wereselected. It is not only intended as a manual for openSMILE users, but also andprimarily as a guide and source of inspiration for students and scientists involvedin the design of speech and music analysis methods that can robustly handlereal-life conditions.. |
| 出版日期 | Book 2016 |
| 关键词 | openSMILE; Speech Emotion Recognition; Voice Analytics; Affective Computing; Acoustic Feature Extraction |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-27299-3 |
| isbn_softcover | 978-3-319-80111-7 |
| isbn_ebook | 978-3-319-27299-3Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer International Publishing Switzerland 2016 |
发表于 2025-3-21 17:53:30
