Abstract
The human activity that takes place in meeting rooms or classrooms is reflected in a rich variety of acoustic events (AE), produced either by the human body or by objects handled by humans, so the determination of both the identity of sounds and their position in time may help to detect and describe that human activity. Indeed, speech is usually the most informative sound, but other kinds of AEs may also carry useful information, for example, clapping or laughing inside a speech, a strong yawn in the middle of a lecture, a chair moving or a door slam when the meeting has just started. Additionally, detection and classification of sounds other than speech may be useful to enhance the robustness of speech technologies like automatic speech recognition.
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Temko, A., Nadeu, C., Macho, D., Malkin, R., Zieger, C., Omologo, M. (2009). Acoustic Event Detection and Classification. In: Waibel, A., Stiefelhagen, R. (eds) Computers in the Human Interaction Loop. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84882-054-8_7
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DOI: https://doi.org/10.1007/978-1-84882-054-8_7
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