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