Search Results for "audio processing"
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Showing 380 open source projects for "audio processing"
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Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. ... -
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OpenVINO AI Plugins for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity. These AI features run 100% locally on your PC, no internet connection is necessary. OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU. -
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Fun Audio Chat
Large Audio Language Model built for natural interactions
Fun Audio Chat is an interactive voice-first conversational AI platform designed to let users engage in natural spoken dialogue with large language models in real time, turning speech into context-aware responses while maintaining a smooth back-and-forth experience. It combines speech recognition, audio processing, and AI generation so users can speak simply and receive spoken replies, enabling applications such as virtual assistants, voice bots, and hands-free chat interfaces. ... -
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Step-Audio 2
Multi-modal large language model designed for audio understanding
Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. ... -
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Ultimate Vocal Remover (UVR5)
GUI for a Vocal Remover that uses Deep Neural Networks
This application uses state-of-the-art source separation models to remove vocals from audio files. UVR's core developers trained all of the models provided in this package (except for the Demucs v3 and v4 4-stem models). -
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Faust
Functional programming language for signal processing
Faust (Functional Audio Stream) is a functional programming language for sound synthesis and audio processing with a strong focus on the design of synthesizers, musical instruments, audio effects, etc. Faust targets high-performance signal processing applications and audio plug-ins for a variety of platforms and standards. The core component of Faust is its compiler. -
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Librosa
Python library for audio and music analysis
Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing. -
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iPlug 2
C++ Audio Plug-in Framework for desktop, mobile, xr and web
iPlug 2 is a cross-platform C++ framework for developing audio plug-ins and applications that can target multiple formats and environments from a single codebase. It abstracts both the audio processing layer and the graphical user interface, allowing developers to focus on signal processing and design while the framework handles platform-specific details. The framework supports a wide range of plug-in standards, including VST, Audio Units, AAX, and newer formats like CLAP, enabling compatibility with major digital audio workstations. ... -
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ffmpeg-normalize
Audio Normalization for Python/ffmpeg
ffmpeg-normalize is a command-line utility designed to normalize audio levels in media files using FFmpeg, ensuring consistent volume across multiple tracks. It supports both EBU R128 loudness normalization and peak normalization methods, allowing users to choose the appropriate standard for their needs. The tool analyzes audio streams and applies adjustments to achieve target loudness levels without introducing distortion. It can process multiple files in batch mode, making it suitable for... -
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Moonshine Voice
Fast and accurate automatic speech recognition (ASR) for edge devices
...The project is designed to enable real-time voice applications such as live transcription, voice commands, and embedded speech interfaces without requiring heavy cloud infrastructure. Its architecture emphasizes low latency and flexible input handling, allowing audio streams of varying durations rather than relying on fixed processing windows. Moonshine supports multiple platforms including mobile, desktop, and embedded systems, and provides example projects to accelerate integration into real-world products. The toolkit also includes specialized model variants, including monolingual options that improve accuracy for specific languages. ... -
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Shutter Encoder
A professional video compression tool accessible to all
Shutter Encoder is a cross-platform video and audio processing application designed to provide professional-grade encoding and conversion tools through an accessible graphical interface. Built primarily on FFmpeg, it offers a wide range of media operations including transcoding, compression, format conversion, and editing. The software supports numerous codecs and formats, enabling users to prepare media for broadcasting, streaming, or archiving. -
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FFBox
A multimedia transcoded treasure chest / a FFmpeg case
FFBox is a graphical multimedia processing application that provides an accessible interface for working with FFmpeg operations such as encoding, conversion, and editing. It allows users to perform tasks like trimming, merging, and compressing media files without using command-line tools. The software supports a wide range of audio and video formats, making it suitable for diverse media workflows. -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. ... -
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mediasoup
Cutting Edge WebRTC Video Conferencing
mediasoup is a Node.js library that provides a cutting-edge WebRTC server capable of handling real-time communications with efficient media routing and processing. -
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PyAV
Pythonic bindings for FFmpeg's libraries
...While powerful, it requires a solid understanding of FFmpeg concepts, as it prioritizes flexibility and control over abstraction. Overall, PyAV is a robust tool for developers building advanced video and audio processing systems in Python. -
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AI-Media2Doc
AI tool converting video/audio into structured documents instantly
AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not uploaded externally. ... -
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ThinkDSP
Digital Signal Processing in Python, by Allen B. Downey
Think DSP is an educational Python project that teaches digital signal processing through executable examples rather than starting with heavy mathematical formalism. It accompanies Allen B. Downey’s book and organizes most lessons as Jupyter notebooks. Readers work directly with waves, spectra, harmonics, filtering, convolution, and other signal-processing concepts. Early exercises show how to decompose sounds, modify frequency components, and synthesize new audio. ... -
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SFBAudioEngine
A powerhouse of audio functionality for macOS, iOS, and tvOS
SFBAudioEngine is an advanced audio engine designed for macOS and iOS, focusing on high-quality playback, precise audio control, and support for a wide range of audio formats. Built for modern Apple platforms, it provides developers with a robust tool for integrating sophisticated audio functionalities into their applications. It emphasizes extensibility, performance, and clean API design. -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. -
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AutoSubSync
Automatic subtitle synchronization tool
AutoSubSync is a cross-platform desktop application designed to automatically synchronize subtitle files with video content using advanced alignment algorithms. It integrates tools like ffsubsync, autosubsync, and alass to analyze audio and match subtitle timing with high accuracy. The application supports both automatic synchronization and manual adjustment, allowing users to fine-tune results when needed. It provides a drag-and-drop interface that simplifies the process of loading video and subtitle files, making it accessible for non-technical users. AutoSubSync also includes batch processing capabilities, enabling users to handle entire media libraries efficiently. ... -
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MediaDevices
Go implementation of the MediaDevices API
mediadevices is a Go library developed by the Pion WebRTC team that enables real-time access to audio and video devices for building native Go applications involving media streaming and conferencing. It provides a cross-platform, unified API for capturing and manipulating media streams and is often used in combination with Pion WebRTC for peer-to-peer communications. Its support for device enumeration, media constraints, and frame processing makes it a powerful building block for custom voice and video solutions in Go. -
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Hugging Face - Speech To Speech
Open speech-to-speech models and pipelines by Hugging Face toolkit AI
This project from Hugging Face focuses on enabling direct speech-to-speech processing using modern machine learning models. It provides tools and reference implementations that allow audio input to be transformed into audio output without requiring an intermediate text representation. Hugging Face - Speech To Speech builds on recent advances in speech modeling, combining components such as speech recognition, translation, and synthesis into unified pipelines. ... -
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Praat
Doing Phonetics By Computer
Praat is a speech analysis application and source repository for doing phonetics by computer. It was created by Paul Boersma and David Weenink at the University of Amsterdam. The software lets researchers, linguists, clinicians, teachers, and students analyze, synthesize, manipulate, and annotate speech recordings. It supports acoustic inspection through waveforms, spectrograms, pitch tracks, formants, intensity, and related phonetic measurements. Praat also includes scripting tools for... -
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Overtone
Collaborative programmable music
Overtone is an open-source audio environment designed to explore new musical ideas from synthesis and sampling to instrument building, live coding and collaborative jamming. We combine the powerful SuperCollider audio engine, with Clojure, a state-of-the-art lisp, to create an intoxicating interactive sonic experience. Synchronize your visuals and noise with ease. -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library.
