Sound Event Detection and Time–Frequency Segmentation from Weakly Labelled Data
نویسندگان
چکیده
منابع مشابه
A joint separation-classification model for sound event detection of weakly labelled data
Source separation (SS) aims to separate individual sources from an audio recording. Sound event detection (SED) aims to detect sound events from an audio recording. We propose a joint separation-classification (JSC) model trained only on weakly labelled audio data, that is, only the tags of an audio recording are known but the time of the events are unknown. First, we propose a separation mappi...
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The work presented in this article studies how the context information can be used in the automatic sound event detection process, and how the detection system can benefit from such information. Humans are using context information to make more accurate predictions about the sound events and ruling out unlikely events given the context. We propose a similar utilization of context information in...
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As there is little doubt that the perception of one’s acoustic environment is mainly driven by noticed sound events, an environmental sound policy approach with a focus on the local urban neighborhood scale should address all noticeable sound events. These sound events have in common that they are not easily predictable, and that they show a very strong spatial variability. Dense urban sound mo...
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Humans can easily segregate and recognize one sound source from an acoustic mixture, and recognize a certain voice from a busy background which includes other people talking and music. Sound event detection and classification aims to process an acoustic signal and convert it into descriptions of the corresponding sound events present at the scene. This is useful, e.g., for automatic tagging in ...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Audio, Speech, and Language Processing
سال: 2019
ISSN: 2329-9290,2329-9304
DOI: 10.1109/taslp.2019.2895254