How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides a suite of tools for extracting musical features, estimating fundamental frequencies, and tracking rhythmic pulses in audio streams. The library specializes in the detection of pitch and beat, enabling the extraction of musical notes and the estimation of overall tempo. It also includes capabilities for automatic onset detection to identify the start of sonic events and the separation of audio signals into percussive transients and steady-state tonal components. The system c
C++ library for audio and music analysis, description and synthesis, including Python bindings
Python speech features is a signal processing toolkit and library for extracting standard speech recognition features from raw audio signals. It provides computational capabilities to calculate mel-frequency cepstral coefficients, raw and log filterbank energies, and spectral subband centroids for automated speech recognition systems and acoustic analysis. The library implements audio signal transformations including pre-emphasis filtering, overlapping windowed frame segmentation, Fast Fourier Transform spectral analysis, mel-filterbank projection with configurable filter weights and frequenc
This library provides a deep learning framework for training neural networks to perform speech recognition and audio classification. It utilizes sequence-to-sequence architectures to map variable-length audio inputs into text or numerical outputs, enabling the development of custom speech-to-text transcription models. The project distinguishes itself through integrated audio processing capabilities that transform raw waveforms into spectrograms and high-dimensional numerical vectors. These tools allow for the extraction of unique vocal characteristics to identify speakers, as well as the clas
Audio features extraction
The main features of yaafe/yaafe are: Computer Audition, Feature Extraction.
Open-source alternatives to yaafe/yaafe include: mtg/essentia — C++ library for audio and music analysis, description and synthesis, including Python bindings. aubio/aubio — Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides… jameslyons/python_speech_features — Python speech features is a signal processing toolkit and library for extracting standard speech recognition features… pannous/tensorflow-speech-recognition — This library provides a deep learning framework for training neural networks to perform speech recognition and audio… bmcfee/muda — A library for augmenting annotated audio data. danilobellini/audiolazy — Expressive Digital Signal Processing (DSP) package for Python.