articleOct 25, 2010GREEN OA

Opensmile

Technical University of Munich

Indexed incrossref

Abstract

We introduce the openSMILE feature extraction toolkit, which unites feature extraction algorithms from the speech processing and the Music Information Retrieval communities. Audio low-level descriptors such as CHROMA and CENS features, loudness, Mel-frequency cepstral coefficients, perceptual linear predictive cepstral coefficients, linear predictive coefficients, line spectral frequencies, fundamental frequency, and formant frequencies are supported. Delta regression and various statistical functionals can be applied to the low-level descriptors. openSMILE is implemented in C++ with no third-party dependencies for the core functionality. It is fast, runs on Unix and Windows platforms, and has a modular,…

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Authors

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Topics & keywords

Keywords
  • Computer science
  • Linear predictive coding
  • Mel-frequency cepstrum
  • Unix
  • Speech recognition
  • Feature extraction
  • Linear prediction
  • Speech processing
UN Sustainable Development Goals
  • Quality Education
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