aubio/aubio
Aubio
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 covers broad spectral analysis areas, including Fast Fourier Transform computation, mel-frequency cepstral coefficients, and mel-band energy extraction. It further provides utilities for temporal analysis, audio resampling, and file input/output operations for loading and slicing audio data.
Features
- Audio Analysis Libraries - Provides a comprehensive set of tools for extracting musical features and performing spectral analysis on digital audio signals.
- Pitch and Beat Detection Tools - Provides a comprehensive toolkit for estimating fundamental frequency and tracking rhythmic pulses in audio streams.
- Audio Spectral Features - Extracts frequency-domain characteristics such as chroma, harmonics, and spectral coefficients from audio signals.
- Music Information Retrieval - Identifies musical notes and extracts MFCCs and spectral coefficients for music information retrieval.
- Beat Tracking - Locates points in an audio signal that correspond to an intuitive rhythmic pulse.
- Sound Event Detection - Locates the exact start times of musical notes or sonic events within recorded sound streams.
- Audio Digital Signal Processing - Modifies audio signals through digital filters, sampling rate changes, and spectral filtering.
- Audio Processing - Handles audio signals using high-precision single and double floating-point formats for accurate processing.
- Tempo Analysis - Calculates the general speed of an audio file measured in beats per minute.
- Audio Event Detection - Identifies the start of musical notes or sonic events using automatic onset detection algorithms.
- Audio Frequency Analysis - Determines the fundamental frequency of musical notes in live or recorded audio streams.
- Audio Onset Detections - A process in the library to identify the beginning of discrete sound events and return specific timestamps.
- Audio Resampling - Converts the sample rate of audio data to different frequencies to ensure consistent signal analysis.
- Pitch Estimation - Estimates the fundamental frequency of an audio signal to determine musical notes.
- Combined Pitch and Tempo Extraction - Extracts the fundamental frequency of a sound while tracking the rhythmic pulse.
- Percussive and Tonal Component Separations - Splits audio signals into percussive and tonal components to allow independent analysis of rhythmic and melodic elements.
- Tempo and Beat Detection - Analyzes rhythmic patterns to calculate overall tempo and locate individual beat positions.
- Spectral Signal Analysis - Uses Fast Fourier Transforms to analyze signal frequency content for pitch and spectral coefficient identification.
- Transient and Steady-State Separations - Splits an audio signal into percussive and tonal components for independent analysis.
- Audio Signal Analysis - Converts sound waves into frequency data and spectral coefficients to analyze audio characteristics.
- Digital Signal Processing Libraries - Implements algorithms for Fourier transforms, resampling, and filtering of floating-point audio samples.
- Fourier Transforms - Performs discrete Fourier transforms on audio signals to analyze frequency components.
- Pitch Extraction - Determines the fundamental frequency of a musical note using specific filtering algorithms.
- Implémentations natives en C - Implements core audio processing logic in C to ensure high performance and low latency for real-time analysis.
- Mel-band Energy Extractions - Computes energy levels across different mel-frequency bands to analyze specific sound characteristics.
- Mel-Frequency Cepstral Coefficients - Implements Mel-Frequency Cepstral Coefficients computation to represent the short-term power spectrum of audio signals.
- Time-Stretching and Pitch-Shifting - Implements phase-vocoder transformations to enable time-stretching and pitch-shifting of audio signals.
- Melody Note Extraction - Identifies sequences of musical notes by combining onset detection and pitch extraction.
- Spectral Coefficients - Provides functions to calculate spectral coefficients representing the short-term power spectrum of sound signals.
- Multi-Language Binding Layers - Provides language bindings that expose the native C engine to high-level scripts for broader accessibility.
- Computer Audition - Library for real-time audio and music analysis.
- Feature Extraction - C-based feature extractor with a Python interface.
- Audio - Library for real-time audio and music analysis.
- Audio Processing - Library for real-time audio and music analysis.
- Audio Processing and Analysis - C library with Python bindings for audio and music feature analysis.
- Windows Environments - Listed in the “Windows Environments” section of the Awesome C awesome list.
