1161 Open source projects that are alternatives of or similar to Surfboard

SincNet is a neural architecture for efficiently processing raw audio samples.

A cross-platform DSP library written in C++ 11/14. This library harnesses the power of C++ templates to implement a complete set of DSP algorithms.

Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.

Keras (tensorflow) implementation of SincNet (Mirco Ravanelli, Yoshua Bengio - https://github.com/mravanelli/SincNet)

Different implementations of "Weighted Prediction Error" for speech dereverberation

Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland. - Mirrored from https://gitlab.idiap.ch/bob/bob

Audio Fingerprinting & Retrieval for .NET

Digital Audio Workstation with Python; VST instruments/effects, parameter automation, and native processors

Speech noise reduction which was generated using existing post-production techniques implemented in Python

A Python library aimed at acousticians.

Demo projects for iOS Audio & Video development.

Sampler, Sequencer, Multi-engine synth and effects - in a box! [WIP]

PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

A collection of Audio and Speech pre-trained models.

A little package that brings sound to any Go application. Suitable for playback and audio-processing.

audio toolkit. 好用的语音处理工具箱，包含语音降噪、音频格式转换、特征频谱生成等模块。

The code for the MaD TwinNet. Demo page:

A library for soundscape synthesis and augmentation

Understanding emotions from audio files using neural networks and multiple datasets.

Open source audio annotation tool for humans™

Your Hardcore Loop Machine.

Automated feature extraction in Python

MNE-CPP: A Framework for Electrophysiology

A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.

Real time monaural source separation base on fully convolutional neural network operates on Time-frequency domain.

Pytorch implementation of subband decomposition

🔉 spafe: Simplified Python Audio Features Extraction

Pitch shifter using WSOLA and resampling implemented by Python3

Fast, modern C++ DSP framework, FFT, Sample Rate Conversion, FIR/IIR/Biquad Filters (SSE, AVX, AVX-512, ARM NEON)

Node based multi effects audio processor

A list of resources and projects to help learn about audio

Python DSP module

Mixing an audio file with a noise file at any Signal-to-Noise Ratio (SNR)

OpenShot Audio Library (libopenshot-audio) is a free, open-source project that enables high-quality editing and playback of audio, and is based on the amazing JUCE library.

Real-time Audio-to-audio Karaoke Generation System for Monaural Music

List of articles related to deep learning applied to music

Encode an image to sound and view it as a spectrogram - turn your images into music

Audio engine and DSP for Android, written in C++ providing low latency performance in a musical context, supporting both OpenSL and AAudio.

Easily transcode media using Node.js 🎶

Package for automatic beat-mixing of music files in Python 🐻🎚

Codebase for RS-MET products (Robin Schmidt's Music Engineering Tools)

Reading list for research topics in multimodal machine learning

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

.NET library for 1D signal processing focused specifically on audio processing

Classification of WAV files from cats and dogs

Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁

Create and edit DDC headset correction files

A convenient way of processing digital signals in F#

ACLEW Diarization Virtual Machine

Algorithms for matching audio file similarities. Mirror of https://git.iem.at/sciss/Strugatzki

AntroPy: entropy and complexity of (EEG) time-series in Python

Feature extraction of speech signal is the initial stage of any speech recognition system.

Python adaptive signal processing tutorials

python speech signal processing library

FFME: The Advanced WPF MediaElement (based on FFmpeg)

MLT Multimedia Framework

This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.

Fast and high quality sample-rate conversion library for Python

A real-time netlist based audio circuit plugin

A Java program to implement a DMTF Decoder.