aubio ===== aubio is a collection of tools for music and audio analysis. This package integrates the aubio library with [NumPy] to provide a set of efficient tools to process and analyse audio signals, including: - read audio from any media file, including videos and remote streams - high quality phase vocoder, spectral filterbanks, and linear filters - Mel-Frequency Cepstrum Coefficients and standard spectral descriptors - detection of note attacks (onset) - pitch tracking (fundamental frequency estimation) - beat detection and tempo tracking aubio works with both Python 2 and Python 3. Built with ---------- The core of aubio is written in C for portability and speed. In addition to [NumPy], aubio can be optionally built to use one or more of the following libraries: - media file reading: - [ffmpeg](https://ffmpeg.org) / [avcodec](https://libav.org) to decode and read audio from almost any format, - [libsndfile](http://www.mega-nerd.com/libsndfile/) to read audio from uncompressed sound files, - [libsamplerate](http://www.mega-nerd.com/SRC/) to re-sample audio signals - [CoreAudio](https://developer.apple.com/reference/coreaudio) to read all media files supported natively on macOS, iOS, and tvOS. - hardware acceleration: - [Atlas](http://math-atlas.sourceforge.net/) and [Blas](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms), for accelerated vector and matrix computations, - [fftw3](http://fftw.org), to compute fast Fourier Transforms of any size. - [Accelerate](https://developer.apple.com/reference/accelerate) for hardware accelerated FFT and matrix computations on macOs and iOS, - [Intel IPP](https://software.intel.com/en-us/intel-ipp), accelerated vector computation and FFT implementation, Documentation ------------- - [module documentation][doc_python] - [installation][doc_python_install] - [aubio manual][manual] - [aubio homepage][homepage] [manual]: https://aubio.org/manual/latest/ [doc_python]: https://aubio.org/manual/latest/python.html [doc_python_install]: https://aubio.org/manual/latest/python_module.html [homepage]: https://aubio.org [NumPy]: https://www.numpy.org Demos scripts ------------- Some examples are available in the [`python/demos`][demos_dir] folder. These scripts are small programs written in python and using python-aubio. **Notes**: installing additional modules is required to run some of the demos. ### Analysis - `demo_source.py` uses aubio to read audio samples from media files - `demo_onset_plot.py` detects attacks in a sound file and plots the results using [matplotlib] - `demo_pitch.py` looks for fundamental frequency in a sound file and plots the results using [matplotlib] - `demo_spectrogram.py`, `demo_specdesc.py`, `demo_mfcc.py` for spectral analysis. ### Real-time - `demo_pyaudio.py` and `demo_tapthebeat.py` use [pyaudio] - `demo_pysoundcard_play.py`, `demo_pysoundcard.py` use [PySoundCard] - `demo_alsa.py` uses [pyalsaaudio] ### Others - `demo_timestretch.py` can change the duration of an input file and write the new sound to disk, - `demo_wav2midi.py` detects the notes in a file and uses [mido] to write the results into a MIDI file ### Example Use `demo_timestretch_online.py` to slow down `loop.wav`, write the results in `stretched_loop.wav`: $ python demo_timestretch_online.py loop.wav stretched_loop.wav 0.92 [demos_dir]:https://github.com/aubio/aubio/tree/master/python/demos [pyaudio]:https://people.csail.mit.edu/hubert/pyaudio/ [PySoundCard]:https://github.com/bastibe/PySoundCard [pyalsaaudio]:https://larsimmisch.github.io/pyalsaaudio/ [mido]:https://mido.readthedocs.io [matplotlib]:https://matplotlib.org/