Search Results for "audio processing"
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Showing 98 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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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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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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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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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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AudioCraft
Audiocraft is a library for audio processing and generation
...It also contains training code and recipes, so researchers can fine-tune on custom data or explore new objectives without building infrastructure from scratch. Example notebooks, CLI tools, and audio utilities help with prompt design, conditioning on reference audio, and post-processing to produce ready-to-share outputs. -
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NovaSR
A lightning fast audio upsampler
...NovaSR is especially valuable for post-processing tasks in speech enhancement, TTS pipelines, and dataset restoration where low sampling rates degrade perceived audio clarity; the minimal model size also makes it suitable for edge and embedded use cases where memory is at a premium. Its performance can reach thousands of times realtime on modern GPUs, allowing massive audio batches to be processed with negligible compute overhead. -
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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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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. ... -
13
Twspace-dl
A python module to download twitter spaces
Twspace-dl is a Python-based tool designed to download audio content from Twitter Spaces, enabling users to archive live or recorded sessions locally. It works by extracting streaming URLs and processing them with FFmpeg to generate downloadable audio files. The tool supports both command-line and graphical interfaces, making it accessible to different types of users. It requires authentication via exported cookies due to API restrictions, ensuring access to protected content. twspace-dl also includes options for saving metadata, playlists, and cover art associated with the stream. ... -
14
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. -
15
WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces... -
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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. ... -
17
ReClip
Download videos from almost any website
...Users can paste multiple URLs at once, select output formats such as MP4 or MP3, and choose quality settings before downloading. The system also includes features like automatic URL deduplication and batch processing to improve usability. -
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Voice-Pro
Comprehensive Gradio WebUI for audio processing
Voice-Pro is the best gradio WebUI for transcription, translation and text-to-speech. It can be easily installed with one click. Create a virtual environment using Miniconda, running completely separate from the Windows system (fully portable). Supports real-time transcription and translation, as well as batch mode. -
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cloud-morph
Decentralize, Self-host Cloud Gaming/Application
cloud-morph is a cloud-based media processing service that enables real-time video and audio transformation using FFmpeg in scalable environments. It is designed to run as a backend service that processes media streams or files and applies transformations such as transcoding, filtering, and format conversion. The system supports API-driven workflows, allowing integration into web applications or automation pipelines. -
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VibeVoice
Open-source multi-speaker long-form text-to-speech model
VibeVoice-1.5B is Microsoft’s frontier open-source text-to-speech (TTS) model designed for generating expressive, long-form, multi-speaker conversational audio such as podcasts. Unlike traditional TTS systems, it excels in scalability, speaker consistency, and natural turn-taking for up to 90 minutes of continuous speech with as many as four distinct speakers. A key innovation is its use of continuous acoustic and semantic speech tokenizers operating at an ultra-low frame rate of 7.5 Hz, enabling high audio fidelity with efficient processing of long sequences. ... -
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal music libraries and generate curated playlists for different moods or listening contexts. ... -
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Videomass
Videomass is a free, open source and cross-platform GUI for FFmpeg
Videomass is a free, open-source graphical interface for FFmpeg designed to make advanced video and audio processing accessible to both beginners and experienced users. Built in Python using wxPython, it provides a cross-platform environment for managing encoding, conversion, and editing tasks through a visual interface. The software supports multitasking operations, allowing users to process multiple media files simultaneously. It offers extensive configuration options while also providing presets to simplify common workflows. ... -
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pyVideoTrans
Translate the video from one language to another and embed dubbing
pyVideoTrans is an ambitious open-source multimedia processing project that assembles speech recognition, subtitle generation, AI translation, voice synthesis, and video assembly into a unified pipeline for converting videos from one language to another with embedded dubbing and captions. At its core it runs speech-to-text models to transcribe audio tracks, translates the resulting text into a target language using local or cloud-based translation engines, synthesizes new speech to match the translated subtitles, and then merges that speech back into the video, creating a fully localized media file. ... -
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WhisperX
Automatic Speech Recognition with Word-level Timestamps
WhisperX is an advanced speech recognition system built on top of OpenAI’s Whisper model, designed to improve transcription accuracy and timing precision for long-form audio. It addresses key limitations of standard Whisper implementations by introducing voice activity detection and forced alignment techniques to produce word-level timestamps. The system enables batched inference, significantly increasing transcription speed while maintaining high accuracy. It is particularly effective for... -
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Insanely Fast Whisper
An opinionated CLI to transcribe Audio files w/ Whisper on-device
Insanely Fast Whisper is a high-performance command-line tool designed to dramatically accelerate speech-to-text transcription using OpenAI’s Whisper models on local hardware. It leverages modern optimizations such as batch processing, mixed precision, and advanced attention mechanisms like Flash Attention to significantly reduce inference time while maintaining high transcription accuracy. The project is built on top of the Transformers ecosystem and integrates with libraries such as Optimum to maximize GPU efficiency. It is specifically engineered for environments with CUDA-enabled GPUs or Apple Silicon devices, allowing users to process hours of audio in minutes or even seconds depending on hardware capabilities. ...
