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openSMILE (open-source Speech and Music Interpretation by Large-space Extraction) is a complete and open-source toolkit for audio analysis, processing and classification especially targeted at speech and music applications, e.g. automatic speech recognition, speaker identification, emotion recognition, or beat tracking and chord detection.

It is written purely in C++, has a fast, efficient, and flexible architecture, and runs on desktop, mobile, and embedded platforms such as Linux, Windows, macOS, Android, iOS and Raspberry Pi.

See also the standalone opensmile Python package for an easy-to-use wrapper if you are working in Python.

Please see our blog post on audeering.com for a summary of the new features in version 3.0.

Pre-built x64 binaries for Windows, Linux, and macOS are provided on the Releases page. Alternatively, you may follow the steps below to build openSMILE yourself, if desired.

For more details on how to customize builds, build for other platforms, and use openSMILE, see Section Get started in the documentation.

Prerequisites:

• A version of gcc and g++ or Clang needs to be installed that supports C++11.
• CMake 3.5.1 or later needs to be installed and in the PATH.

1. In build_flags.sh, set build flags and options as desired.
2. Run bash build.sh.

Build files will be generated in the ./build subdirectory. You can find the main SMILExtract binary in ./build/progsrc/smilextract.

Prerequisites:

• Visual Studio 2017 or higher with C++ components is required.
• CMake 3.15 or later needs to be installed and in the PATH.

1. In build_flags.ps1, set build flags and options as desired.
2. Run powershell -ExecutionPolicy Bypass -File build.ps1.

Build files will be generated in the ./build subdirectory. You can find the main SMILExtract.exe binary in ./build/progsrc/smilextract.

You can find extensive documentation with step-by-step instructions on how to build openSMILE and get started at https://audeering.github.io/opensmile/.

The toolkit was first developed at the Institute for Human-Machine Communication at the Technische Universität München in Munich, Germany. It was started within the SEMAINE EU-FP7 research project. The toolkit is now owned and maintained by audEERING GmbH, who provide intelligent audio analysis solutions, automatic speech emotion recognition, and paralinguistic speech analysis software packages as well as consulting and development services on these topics.

We welcome contributions! For feedback and technical support, please use the issue tracker.

openSMILE follows a dual-licensing model. Since the main goal of the project is widespread use of the software to facilitate research in the field of machine learning from audio-visual signals, the source code, and binaries are freely available for private, research, and educational use under an open-source license (see LICENSE). It is not allowed to use the open-source version of openSMILE for any sort of commercial product. Fundamental research in companies, for example, is permitted, but if a product is the result of the research, we require you to buy a commercial development license. Contact us at [email protected] (or visit us at https://www.audeering.com) for more information.

Original authors: Florian Eyben, Felix Weninger, Martin Wöllmer, Björn Schuller
Copyright © 2008-2013, Institute for Human-Machine Communication, Technische Universität München, Germany
Copyright © 2013-2015, audEERING UG (haftungsbeschränkt)
Copyright © 2016-2023, audEERING GmbH

Please cite openSMILE in your publications by citing the following paper:

Florian Eyben, Martin Wöllmer, Björn Schuller: "openSMILE - The Munich Versatile and Fast Open-Source Audio Feature Extractor", Proc. ACM Multimedia (MM), ACM, Florence, Italy, ISBN 978-1-60558-933-6, pp. 1459-1462, 25.-29.10.2010.