8 Best Python Sound Processing Libraries

Here are the best open-source Python sound-processing libraries for your applications. You can use them to build web and smartphone applications with audio analysis, synthesis, and manipulation functions.

These libraries provide powerful tools for sound processing in Python, such as reading and writing sound files, support for a wide range of file formats, and more with a simple and efficient interface for loading and saving audio data. With these libraries, developers get a wide range of tools for audio analysis, including feature extraction, segmentation, and representation, along with support for loading and saving various audio file formats. These Python libraries also support various audio formats, allowing developers to perform tasks such as cutting, concatenating, and exporting audio files. These open-source coding components are widely used in music information retrieval and audio signal processing research.

We have handpicked top and trending open-source Python sound-processing libraries for your next project. They offer a variety of easy-to-use interfaces for manipulating and processing audio files.

Librosa:

• Used for music and audio analysis.
• Offers features for beat tracking, melody extraction, and sound decomposition.
• Supports Linux, Mac, and Windows operating systems.

SoundFile:

• Used for reading and writing audio files.
• Supports a wide range of formats and sample rates.
• Based on libsndfile, CFFI, and NumPy libraries.

Pydub:

• Used for working with audio as a sequence of frames.
• Offers features like playback, mixing, and processing.
• Provides a simple and easy high-level interface for audio manipulation and processing.

PySoundCard

• Used for accessing sound card hardware.
• Features include audio input and output and control of audio parameters.
• Can play and record audio data as well.
• Based on PortAudio, CFFI, and NumPy libraries.

Madmom:

• Used for music and audio analysis, signal processing, etc.
• Features include beat tracking, chord recognition, and onset detection algorithms.
• Has a strong focus on music information retrieval (MIR) tasks.

music21:

• Used for music theory, analysis, and composition.
• Capabilities include capabilities for parsing, editing, and generating musical scores.
• Offers a toolkit for Computer-Aided Musical Analysis and Computational Musicology.

Aubio:

• Used for real-time audio signal processing.
• Features include pitch detection, onset detection, and beat-tracking algorithms.
• Allows audio labeling: pitch, onset, tempo tracking, and more.

Audio:

• Used for data manipulation and transformation for audio signal processing.
• Supports multiple audio input formats.
• Based on PyTorch library.