With Python Libraries, you can easily manipulate and process any type of audio you like. You can use these audio libraries for creating a different types of sound effects for your audio.
Audio Manipulation with Python:-
Python makes audio manipulation easy and makes the process simple for you. you can use a few lines of code and import some methods that someone else has created for you. I will mention some of the best python libraries that can help you in audio manipulation and audio processing.
There is a huge list of Python Libraries that can be used for audio manipulation. I will list 13 Python Libraries that are used for audio Manipulation and Metadata Extraction. Pick the one that suits you.
librosa is a python package for music and audio analysis. It provides the building blocks necessary to create music information retrieval systems.
matchering is a Python Library for audio matching and mastering. You can make your music instantly sound like your favorite artist’s music. You can make all the tracks on your new album sound the same very quickly. You can find new aspects of your sound in experiments.
audioread help you Decode audio files using whichever backend is available. The library currently supports Gstreamer, Core Audio, MAD, FFmpeg. Each buffer is a bytes-like object (buffer, bytes, or byte array) containing raw 16-bit little-endian signed integer PCM data. (Currently, these PCM format parameters are not configurable, but this could be added to most of the backends.
Dejavu can memorize audio by listening to it once and fingerprinting it. Then by playing a song and recording microphone input or reading from disk, Dejavu attempts to match the audio against the fingerprints held in the database, returning the song being played.
Kapre Preprocess your audio dataset. Resample the audio to the right sampling rate and store the audio signals (waveforms). In your ML model, add Kapre layer e.g. kapre.time_frequency.STFT() as the first layer of the model. The data loader simply loads audio signals and feed them into the model In your hyperparameter search, include DSP parameters like n_fft to boost the performance. When deploying the final model, all you need to remember is the sampling rate of the signal. No dependency or preprocessing!
mingus is an advanced, cross-platform music theory and notation package for Python with MIDI file and playback support. It can be used to play around with music theory, to build editors, educational tools, and other applications that need to process and/or play music. It can also be used to create sheet music with LilyPond.
pyAudioAnalysis helps you audio feature extraction, classification, segmentation, and applications. mingus is a package for Python used by programmers, musicians, composers and researchers to make and analyse music.
pydub helps you Manipulate audio with a simple and easy high level interface. You can Make the beginning louder and the end quieter.
TimeSide is a python framework enabling low and high level audio analysis, imaging, transcoding, streaming and labeling. Its high-level API is designed to enable complex processing on very large datasets of any audio or video assets with a plug-in architecture, a secure scalable backend and an extensible dynamic web frontend.
Beets is the media library management system for obsessive music geeks. The purpose of beets is to get your music collection right once and for all. It catalogs your collection, automatically improving its metadata as it goes. It then provides a bouquet of tools for manipulating and accessing your music.
eyeD3 is a Python tool for working with audio files, specifically MP3 files containing ID3 metadata (i.e. song info). It provides a command-line tool (eyeD3) and a Python library (import eyed3) that can be used to write your own applications or plugins that are callable from the command-line tool.
Mutagen is a Python module to handle audio metadata. It supports ASF, FLAC, MP4, Monkey’s Audio, MP3, Musepack, Ogg Opus, Ogg FLAC, Ogg Speex, Ogg Theora, Ogg Vorbis, True Audio, WavPack, OptimFROG, and AIFF audio files. All versions of ID3v2 are supported, and all standard ID3v2.4 frames are parsed. It can read Xing headers to accurately calculate the bitrate and length of MP3s. ID3 and APEv2 tags can be edited regardless of audio format. It can also manipulate Ogg streams on an individual packet/page level.
tinytag is a library for reading music meta data of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and Wave files with python.
Summary and Conclusion:-
These 13 Libraries will help you use python to manipulate audio. If you have any questions please let me know in the comment section. If you are interested in other python tutorials please visit my youtube channel Code with Ali.