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M. Battermann, S. Heise, and J. Loviscach, "SonoSketch: Querying Sound Effect Databases through Painting," Paper 7794, (2009 May.). doi: M. Battermann, S. Heise, and J. Loviscach, "SonoSketch: Querying Sound Effect Databases through Painting," Paper 7794, (2009 May.). doi:
Abstract: Numerous techniques support finding sounds that are acoustically similar to a given one. It is hard, however, to find a sound to start the similarity search with. Inspired by systems for image search that allow drawing the shape to be found, we address quick input for audio retrieval. In our system, the user literally sketches a sound effect, placing curved strokes on a canvas. Each of these represents one sound from a collection of basic sounds. The audio feed-back is interactive, as is the continuous update of the list of retrieval results. The retrieval is based on symbol se-quences formed from MFCC data compared with the help of a neural net using an editing distance to allow small temporal changes.

@article{battermann2009sonosketch:,
author={battermann, michael and heise, sebastian and loviscach, jörn},
journal={journal of the audio engineering society},
title={sonosketch: querying sound effect databases through painting},
year={2009},
volume={},
number={},
pages={},
doi={},
month={may},} @article{battermann2009sonosketch:,
author={battermann, michael and heise, sebastian and loviscach, jörn},
journal={journal of the audio engineering society},
title={sonosketch: querying sound effect databases through painting},
year={2009},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={numerous techniques support finding sounds that are acoustically similar to a given one. it is hard, however, to find a sound to start the similarity search with. inspired by systems for image search that allow drawing the shape to be found, we address quick input for audio retrieval. in our system, the user literally sketches a sound effect, placing curved strokes on a canvas. each of these represents one sound from a collection of basic sounds. the audio feed-back is interactive, as is the continuous update of the list of retrieval results. the retrieval is based on symbol se-quences formed from mfcc data compared with the help of a neural net using an editing distance to allow small temporal changes.},}

TY - paper
TI - SonoSketch: Querying Sound Effect Databases through Painting
SP - EP -
AU - Battermann, Michael
AU - Heise, Sebastian
AU - Loviscach, Jörn
PY - 2009
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2009 TY - paper
TI - SonoSketch: Querying Sound Effect Databases through Painting
SP - EP -
AU - Battermann, Michael
AU - Heise, Sebastian
AU - Loviscach, Jörn
PY - 2009
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2009
AB - Numerous techniques support finding sounds that are acoustically similar to a given one. It is hard, however, to find a sound to start the similarity search with. Inspired by systems for image search that allow drawing the shape to be found, we address quick input for audio retrieval. In our system, the user literally sketches a sound effect, placing curved strokes on a canvas. Each of these represents one sound from a collection of basic sounds. The audio feed-back is interactive, as is the continuous update of the list of retrieval results. The retrieval is based on symbol se-quences formed from MFCC data compared with the help of a neural net using an editing distance to allow small temporal changes.