• 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