DocumentCode :
166224
Title :
Automatic detection of microphone handling noise
Author :
Kendrick, Paul ; Cox, Trevor J. ; Li, Francis F. ; Fazenda, Bruno M. ; Jackson, Iain R.
Author_Institution :
Acoust. Res. Centre, Univ. of Salford, Salford, UK
fYear :
2014
fDate :
26-28 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
Microphone handling noise is a common problem with user-generated content. It can occur when the operator inadvertently knocks or brushes a recording device. Handling noise may be impulsive, where a microphone is knocked, or a more sustained rubbing noise, when the microphone is brushed against something. A detector able to accurately detect handling noises caused by rubbing while recording speech, music or quotidian sounds has been developed. Ensembles of decision trees were trained to classify handling noise level over 23 ms frames; a second ensemble flags frames when the noise may be masked by foreground audio. Aggregation of the detection over 1 s yielded a Matthews correlation coefficient of 0.91.
Keywords :
audio signal processing; decision trees; microphones; signal detection; Matthews correlation coefficient; brushes; decision trees; ensemble flags frames; knocks; microphone handling noise automatic detection; music; quotidian sounds; recording device; recording speech; sustained rubbing noise; user-generated content; Decision trees; Detectors; Hidden Markov models; Microphones; Noise; Noise level; Training; bagging decision trees; microphone handling noise; noise detector; sound quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Information Processing (CIP), 2014 4th International Workshop on
Conference_Location :
Copenhagen
Type :
conf
DOI :
10.1109/CIP.2014.6844501
Filename :
6844501
Link To Document :
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