Detail publikace

DEEP LEARNING BASED SOUND EVENT RECOGNITION

BAJZÍK, J.

Originální název

DEEP LEARNING BASED SOUND EVENT RECOGNITION

Anglický název

DEEP LEARNING BASED SOUND EVENT RECOGNITION

Jazyk

en

Originální abstrakt

The main paper deals with the analysis of the methods of processing and recognition of events in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots placed in a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. For events classification and class recognition, the freely available machine learning framework TensorFlow is used.

Anglický abstrakt

The main paper deals with the analysis of the methods of processing and recognition of events in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots placed in a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. For events classification and class recognition, the freely available machine learning framework TensorFlow is used.

Dokumenty

BibTex


@inproceedings{BUT162316,
  author="Jakub {Bajzík}",
  title="DEEP LEARNING BASED SOUND EVENT RECOGNITION",
  annote="The main paper deals with the analysis of the methods of processing and recognition of events in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots placed in a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. For events classification and class recognition, the freely available machine learning framework TensorFlow is used.",
  address="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  chapter="162316",
  howpublished="online",
  institution="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  year="2019",
  month="april",
  pages="1--4",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  type="conference paper"
}