Best AI tools for< Split Vocals >

LALAL.AI is a next-generation vocal remover and music source separation service that offers fast, easy, and precise stem extraction. It allows users to remove vocals, instrumental tracks, drums, bass, guitar, synth, string, and wind instruments without quality loss. The platform features advanced AI technology for stem splitting, voice cleaning, voice changing, echo and reverb removal, and lead/back vocal separation. Users can choose from various pricing packages for individual and business use, with options for fast processing, batch uploads, and stem downloads. LALAL.AI also provides detailed FAQs and tips on improving stem-splitting quality.

StemRoller is an AI-powered application that allows users to create stems, instrumental, or acapella versions of any song. Users can simply type the name of a song into the search bar, and StemRoller will find the song online and split it into vocals, drums, bass, and other stems. Additionally, an instrumental track is created with all non-vocal stems mixed down into one track. StemRoller is free and open-source, utilizing Facebook's advanced AI and machine learning research project Demucs. Users can also donate to support the app and receive assistance on Discord for any issues or questions.

Vocalremover.org is a website that offers a tool to remove vocals from music tracks. Users can upload their music files and the tool will process them to create a version without vocals. The site aims to provide a simple and efficient solution for musicians, DJs, and music enthusiasts who want to create karaoke tracks, remixes, or practice with instrumental versions of songs. Vocalremover.org ensures security by verifying user connections and requires enabling JavaScript and cookies for a seamless experience.

SplitSong.com is an AI tool that allows users to split songs into individual instrument tracks using Artificial Intelligence. Users can upload their songs or extract them from YouTube, and the tool separates the tracks such as drums, keyboards, guitars, bass, and vocals. Created by @markdoppler_, SplitSong simplifies the process of isolating specific instrument tracks from a song, making it ideal for musicians, producers, and music enthusiasts.

Music Demixer is an AI-powered application that offers advanced stem separation and automatic music transcription features. It allows users to effortlessly isolate vocals, drums, bass, melody, guitar, and piano in music tracks. The tool provides precise MIDI file generation and ensures 100% privacy by operating offline in the browser. Music Demixer is perfect for musicians, DJs, producers, and creators looking for a simple and superior solution for music editing and analysis.

Gaudio Studio is an AI music separation tool designed for creators to unleash their creativity with ease. It allows users to extract background music, separate instruments, and remove vocals from any music content. Powered by GSEP (Gaudio source SEParation), a high-quality and easy-to-use AI stem separation model, Gaudio Studio offers a seamless experience for audio separation. Users can upload their songs in various formats, access the tool from desktop or mobile devices, and enjoy Studio Plans for advanced processing. Additionally, Gaudio Studio can be integrated with cloud APIs and On-device SDKs for business applications, offering a versatile solution for music professionals and enthusiasts.

Melody ML is an AI-powered music processing tool that allows users to separate music tracks using machine learning technology. Users can upload songs, and the tool uses AI algorithms to extract vocals, drums, bass, and other instruments into separate stems. Melody ML offers a user-friendly platform for music enthusiasts, producers, and artists to enhance their music production process.

Jamorphosia is an AI-powered application that allows users to remove instruments from a song. With advanced technology and audio separation capabilities, users can easily extract vocals, isolate specific instruments, and create custom backing tracks. The tool transforms audio files into personalized songs, suitable for practice or performance. Jamorphosia enhances the music experience by providing a platform for musicians to engage with original tracks in a more immersive way.

Splitter.ai is an AI-driven audio processing platform developed by a Swedish research company. It offers advanced audio processing technologies, including stem separation/extraction, reverb removal, and direct YouTube splitting. The platform is designed to assist music producers, DJs, artists, forensics engineers, audio engineers, karaoke enthusiasts, police, scientists, and more in enhancing their audio processing tasks. Splitter.ai aims to provide high-quality services through AI-driven solutions to meet the diverse needs of its users.

MakeBestMusic is an AI-powered music production suite that allows users to create unique music with just one click using advanced AI technology. The platform offers features such as creating instrumental and vocal music by providing simple descriptive words or lyrics, remixing music by uploading audio files and providing remix descriptions, and splitting music files to extract drums and vocals. MakeBestMusic provides a versatile approach to music creation, catering to both instrumental and vocal preferences with ease. Users can generate dynamic music, remix original audio files, and extract sounds from background music using the powerful AI music tool.

GenerateSongAI is an advanced AI music production tool that revolutionizes the way music creators generate high-quality songs effortlessly. With GenerateSongAI, users can create fully produced songs with just a simple text description or lyrics, customize music styles, extract vocals and instruments, remix existing audio files, and share their music across social platforms. The platform offers a seamless and intuitive experience for music production, catering to a wide range of users from indie filmmakers to content creators, without the need for technical expertise. GenerateSongAI unlocks endless possibilities for creating songs, limited only by the user's imagination.

MJSplitter is a free online tool that allows users to split their Midjourney Grid images into single images. Users can either paste or upload their image grid, and the tool will automatically split the images and save them as JPEGs. The tool is not affiliated with Midjourney, and images are deleted from the server after 24 hours.

Doclingo is an AI-powered document translation tool that supports translating documents in various formats such as PDF, Word, Excel, PowerPoint, SRT subtitles, ePub ebooks, AR&ZIP packages, and more. It utilizes large language models to provide accurate and professional translations, preserving the original layout of the documents. Users can enjoy a limited-time free trial upon registration, with the option to subscribe for more features. Doclingo aims to offer high-quality translation services through continuous algorithm improvements.

AdCopy is an AI-powered advertising platform that helps businesses create high-quality ads and optimize their ad campaigns. The platform uses AI to generate ad copy, create ad creatives, and provide insights into ad performance. AdCopy is designed to help businesses save time and money on their advertising campaigns, while also improving their results.

SplitMyExpenses is an AI-powered application designed to simplify shared expenses with friends. It allows users to create groups, split bills, track debts, and settle up with integrated payment apps. The app offers modern design, AI receipt itemization, friend data powered by payment apps, and beautiful spending charts. With over 150 supported currencies, secure handling of data, and a user-friendly interface, SplitMyExpenses revolutionizes the age-old problem of bill splitting.

SplitParty is an AI-powered application that simplifies the process of splitting complicated bills with friends. Users can easily split a bill by taking a photo of the receipt, allowing the AI to identify items, quantities, and prices. The application enables users to add friends, select items ordered, and split the bill effortlessly. SplitParty Plus offers additional features such as creating groups, saving bill history, and more. Developed by @dqnamo, SplitParty is a bootstrapped indie product designed to streamline bill-splitting experiences.

SanptoBook is a personal accounting software designed to help individuals manage their finances efficiently. It offers features such as invoice and receipt management, reimbursement facilitation, tax filing assistance, bill splitting, and project tracking. The application aims to simplify financial tasks and improve overall financial organization for users. With AI-powered efficiency, SnaptoBook provides state-of-the-art receipt recognition technology and secure cloud storage for all receipts.

promptoMANIA is an AI art community and prompt generator that allows users to create AI images using various diffusion models like CF Spark, Midjourney, and Stable Diffusion. Users can generate high-quality and detailed AI art by providing prompts and selecting different styles and references. The platform offers a user-friendly prompt builder and tools like Grid Splitter to enhance the AI art creation experience. promptoMANIA is a free online tool with no subscription or sign-up required.

GitBrain is an AI-powered Git client designed for Mac users. It simplifies the Git workflow by offering features such as AI commit messages, code splitting, self-code review, auto-detection of projects from favorite IDEs, and a keyboard-friendly design. The application aims to enhance developer productivity by intelligently managing code changes and providing a seamless Git management experience. GitBrain is optimized for Mac performance with a native UI, lightweight design, and customizable themes.

HiPDF is a free online PDF solution that offers a wide range of tools for editing, converting, compressing, and organizing PDFs. It also includes AI-powered tools such as Chat with PDF and AI Detector. With HiPDF, you can easily edit PDFs in your browser, convert PDFs to and from other formats, compress PDFs to reduce their size, and merge, split, and extract images from PDFs. You can also protect your PDFs with passwords and redact sensitive information. HiPDF is a convenient and easy-to-use tool that can help you with all your PDF needs.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

The 'ai-audio-startups' repository is a community list of startups working with AI for audio and music tech. It includes a comprehensive collection of tools and platforms that leverage artificial intelligence to enhance various aspects of music creation, production, source separation, analysis, recommendation, health & wellbeing, radio/podcast, hearing, sound detection, speech transcription, synthesis, enhancement, and manipulation. The repository serves as a valuable resource for individuals interested in exploring innovative AI applications in the audio and music industry.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Easy Voice Toolkit is a toolkit based on open source voice projects, providing automated audio tools including speech model training. Users can seamlessly integrate functions like audio processing, voice recognition, voice transcription, dataset creation, model training, and voice conversion to transform raw audio files into ideal speech models. The toolkit supports multiple languages and is currently only compatible with Windows systems. It acknowledges the contributions of various projects and offers local deployment options for both users and developers. Additionally, cloud deployment on Google Colab is available. The toolkit has been tested on Windows OS devices and includes a FAQ section and terms of use for academic exchange purposes.

RVC_CLI is a command line interface tool for retrieval-based voice conversion. It provides functionalities for installation, getting started, inference, training, UVR, additional features, and API integration. Users can perform tasks like single inference, batch inference, TTS inference, preprocess dataset, extract features, start training, generate index file, model extract, model information, model blender, launch TensorBoard, download models, audio analyzer, and prerequisites download. The tool is built on various projects like ContentVec, HIFIGAN, audio-slicer, python-audio-separator, RMVPE, FCPE, VITS, So-Vits-SVC, Harmonify, and others.

UltraSinger is a tool under development that automatically creates UltraStar.txt, midi, and notes from music. It pitches UltraStar files, adds text and tapping, creates separate UltraStar karaoke files, re-pitches current UltraStar files, and calculates in-game score. It uses multiple AI models to extract text from voice and determine pitch. Users should mention UltraSinger in UltraStar.txt files and only use it on Creative Commons licensed songs.

AI-Song-Cover-RVC is an all-in-one repository that provides tools for downloading YouTube WAV files, separating vocals, splitting audio, training models, and performing inference using Google Colab or Kaggle. The repository offers tutorials in Indonesian for training and inference tasks. Users can access various tools and resources for processing audio data and generating song covers. The repository aims to simplify the process of working with audio data for music-related projects.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Chonkie is a lightweight and fast RAG chunking library designed to efficiently split text for RAG (Retrieval-Augmented Generation) applications. It offers various chunking methods like TokenChunker, WordChunker, SentenceChunker, SemanticChunker, SDPMChunker, and an experimental LateChunker. Chonkie is feature-rich, easy to use, fast, supports multiple tokenizers, and comes with a cute pygmy hippo mascot. It aims to provide a no-nonsense solution for chunking text without the need to worry about dependencies or bloat.

ebook2audiobook is a CPU/GPU converter tool that converts eBooks to audiobooks with chapters and metadata using tools like Calibre, ffmpeg, XTTSv2, and Fairseq. It supports voice cloning and a wide range of languages. The tool is designed to run on 4GB RAM and provides a new v2.0 Web GUI interface for user-friendly interaction. Users can convert eBooks to text format, split eBooks into chapters, and utilize high-quality text-to-speech functionalities. Supported languages include Arabic, Chinese, English, French, German, Hindi, and many more. The tool can be used for legal, non-DRM eBooks only and should be used responsibly in compliance with applicable laws.

Sonic 3 A.I.R. is a non-profit fan game project that provides source code including dependencies for "Sonic 3 - Angel Island Revisited," a fan-made remaster of Sonic 3 & Knuckles. The project is split into several different projects, including external dependencies, librmx libraries, Lemonscript language library, Oxygen Engine, and S3AIR-specific C++ code. To build for different platforms, refer to the readme files in the respective subdirectories of "Oxygen/sonic3air/build." External libraries and code used in this project include SDL2, libogg & libvorbis, zlib, libcurl, jsoncpp, GLEW, Sound chip emulation related code from Genesis Plus GX, Discord Game SDK, xBRZ upscaler shader code, and Hqx upscaler shader code & data files.

ExtractThinker is a library designed for extracting data from files and documents using Language Model Models (LLMs). It offers ORM-style interaction between files and LLMs, supporting multiple document loaders such as Tesseract OCR, Azure Form Recognizer, AWS TextExtract, and Google Document AI. Users can customize extraction using contract definitions, process documents asynchronously, handle various document formats efficiently, and split and process documents. The project is inspired by the LangChain ecosystem and focuses on Intelligent Document Processing (IDP) using LLMs to achieve high accuracy in document extraction tasks.

Tribe AI is a low code tool designed to rapidly build and coordinate multi-agent teams. It leverages the langgraph framework to customize and coordinate teams of agents, allowing tasks to be split among agents with different strengths for faster and better problem-solving. The tool supports persistent conversations, observability, tool calling, human-in-the-loop functionality, easy deployment with Docker, and multi-tenancy for managing multiple users and teams.

PINNACLE is a flexible geometric deep learning approach that trains on contextualized protein interaction networks to generate context-aware protein representations. It provides protein representations split across various cell-type contexts from different tissues and organs. The tool can be fine-tuned to study the genomic effects of drugs and nominate promising protein targets and cell-type contexts for further investigation. PINNACLE exemplifies the paradigm of incorporating context-specific effects for studying biological systems, especially the impact of disease and therapeutics.

LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by the MMRazor and MMDeploy teams. It has the following core features: * **Efficient Inference** : LMDeploy delivers up to 1.8x higher request throughput than vLLM, by introducing key features like persistent batch(a.k.a. continuous batching), blocked KV cache, dynamic split&fuse, tensor parallelism, high-performance CUDA kernels and so on. * **Effective Quantization** : LMDeploy supports weight-only and k/v quantization, and the 4-bit inference performance is 2.4x higher than FP16. The quantization quality has been confirmed via OpenCompass evaluation. * **Effortless Distribution Server** : Leveraging the request distribution service, LMDeploy facilitates an easy and efficient deployment of multi-model services across multiple machines and cards. * **Interactive Inference Mode** : By caching the k/v of attention during multi-round dialogue processes, the engine remembers dialogue history, thus avoiding repetitive processing of historical sessions.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

CompressAI-Vision is a tool that helps you develop, test, and evaluate compression models with standardized tests in the context of compression methods optimized for machine tasks algorithms such as Neural-Network (NN)-based detectors. It currently focuses on two types of pipeline: Video compression for remote inference (`compressai-remote-inference`), which corresponds to the MPEG "Video Coding for Machines" (VCM) activity. Split inference (`compressai-split-inference`), which includes an evaluation framework for compressing intermediate features produced in the context of split models. The software supports all the pipelines considered in the related MPEG activity: "Feature Compression for Machines" (FCM).

Booster is a powerful inference accelerator designed for scaling large language models within production environments or for experimental purposes. It is built with performance and scaling in mind, supporting various CPUs and GPUs, including Nvidia CUDA, Apple Metal, and OpenCL cards. The tool can split large models across multiple GPUs, offering fast inference on machines with beefy GPUs. It supports both regular FP16/FP32 models and quantised versions, along with popular LLM architectures. Additionally, Booster features proprietary Janus Sampling for code generation and non-English languages.

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