학술논문

Automatic detection of microphone handling noise
Document Type
Conference
Source
2014 4th International Workshop on Cognitive Information Processing (CIP) Cognitive Information Processing (CIP), 2014 4th International Workshop on. :1-6 May, 2014
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Noise
Detectors
Hidden Markov models
Training
Microphones
Decision trees
Noise level
noise detector
bagging decision trees
sound quality
microphone handling noise
Language
ISSN
2327-1671
2327-1698
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.