TUT database for acoustic scene classification and sound event detection. Mesaros, A., Heittola, T., & Virtanen, T. In 2016 24th European Signal Processing Conference (EUSIPCO), pages 1128-1132, Aug, 2016.
TUT database for acoustic scene classification and sound event detection [pdf]Paper  doi  abstract   bibtex   
We introduce TUT Acoustic Scenes 2016 database for environmental sound research, consisting of binaural recordings from 15 different acoustic environments. A subset of this database, called TUT Sound Events 2016, contains annotations for individual sound events, specifically created for sound event detection. TUT Sound Events 2016 consists of residential area and home environments, and is manually annotated to mark onset, offset and label of sound events. In this paper we present the recording and annotation procedure, the database content, a recommended cross-validation setup and performance of supervised acoustic scene classification system and event detection baseline system using mel frequency cepstral coefficients and Gaussian mixture models. The database is publicly released to provide support for algorithm development and common ground for comparison of different techniques.
@InProceedings{7760424,
  author = {A. Mesaros and T. Heittola and T. Virtanen},
  booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
  title = {TUT database for acoustic scene classification and sound event detection},
  year = {2016},
  pages = {1128-1132},
  abstract = {We introduce TUT Acoustic Scenes 2016 database for environmental sound research, consisting of binaural recordings from 15 different acoustic environments. A subset of this database, called TUT Sound Events 2016, contains annotations for individual sound events, specifically created for sound event detection. TUT Sound Events 2016 consists of residential area and home environments, and is manually annotated to mark onset, offset and label of sound events. In this paper we present the recording and annotation procedure, the database content, a recommended cross-validation setup and performance of supervised acoustic scene classification system and event detection baseline system using mel frequency cepstral coefficients and Gaussian mixture models. The database is publicly released to provide support for algorithm development and common ground for comparison of different techniques.},
  keywords = {audio recording;audio signal processing;TUT database;acoustic scene classification;sound event detection;environmental sound research;binaural recordings;mel frequency cepstral coefficients;Gaussian mixture models;Event detection;Databases;Automobiles;Signal processing;Mel frequency cepstral coefficient;Europe},
  doi = {10.1109/EUSIPCO.2016.7760424},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570251932.pdf},
}
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