# Music Generation

MakeSong is an innovative AI song generator that can quickly create high-quality music based on user-provided text or lyrics. It offers endless possibilities for music creators, whether they are producing personal works, commercial advertisements, or background music for social media content. The product supports multiple music styles and offers different pricing plans to suit various user needs.

Generator AI Music is an AI music generation tool that uses advanced artificial intelligence technology to help users easily make songs, convert text into music, remove vocals, split tracks, and remix. Product pricing includes free, subscription-based, and other options, suitable for music production enthusiasts, musicians, creators, etc.

The ImagineArt AI tool is an AI art generation tool that uses advanced AI technology to turn text descriptions into vivid image works. Its main advantages include quick image generation, high flexibility, user-friendly, and it is positioned to provide users with creative inspiration and image generation solutions.

Lyria 2 is the latest music generation model capable of creating high-fidelity music in various styles, suitable for complex musical works. This model not only provides powerful tools for music creators but also drives the development of music generation technology, improving creative efficiency. Lyria 2 aims to make music creation simpler and more accessible, providing flexible creative support for both professional musicians and amateurs.

NotaGen is an innovative symbolic music generation model that enhances music generation quality through three stages: pre-training, fine-tuning, and reinforcement learning. Utilizing large language model technology, it can generate high-quality classical music scores, bringing new possibilities to music creation. The model's main advantages include efficient generation, diverse styles, and high-quality output. It is applicable in music creation, education, and research, with broad application prospects.

DiffRhythm is an innovative music generation model that utilizes latent diffusion technology to achieve fast and high-quality full-song generation. This technology breaks through the limitations of traditional music generation methods, eliminating the need for complex multi-stage architectures and cumbersome data preparation. Only lyrics and style prompts are needed to generate a complete song up to 4 minutes and 45 seconds in a short time. Its autoregressive structure ensures fast inference speed, greatly improving the efficiency and scalability of music creation. The model was jointly developed by the Audio, Speech, and Language Processing group (ASLP@NPU) at Northwestern Polytechnical University and the Big Data Institute of the Chinese University of Hong Kong (Shenzhen), aiming to provide a simple, efficient, and creative solution for music creation.

InspireMusic is an AIGC toolkit and model framework focused on music, songs, and audio generation, developed using PyTorch. It achieves high-quality music generation through audio tokenization and decoding processes, combining autoregressive transformers and conditional flow matching models. This toolkit supports multiple conditional controls such as text prompts, music styles, and structures, enabling the generation of high-quality audio at both 24kHz and 48kHz, as well as supporting long audio generation. Additionally, it offers convenient fine-tuning and inference scripts for users to adjust the model according to their needs. The open-source nature of InspireMusic aims to empower everyday users to enhance sound effects in their research through music creation.

YuE is a groundbreaking open-source foundational model series designed for music generation, capable of transforming lyrics into complete songs. It generates full songs featuring captivating vocals and accompanying instrumentals, supporting various music styles. Based on deep learning technology, it boasts powerful generating capability and flexibility, providing music creators with robust tool support. Its open-source nature also allows researchers and developers to conduct further research and development.

YuE is an open-source music generation model developed by the Hong Kong University of Science and Technology and a multimodal art projection team. It can generate full songs up to 5 minutes long, including vocals and accompaniment, based on given lyrics. The model addresses the complex issues of lyric-to-song generation through various technological innovations, such as semantic-enhanced audio taggers, dual-tagging technology, and lyrical chain thinking. The main advantages of YuE include its ability to produce high-quality musical works and support for multiple languages and music styles, offering strong scalability and controllability. The model is currently free and open-source, aimed at promoting the advancement of music generation technology.

The AI Music Generator is an online platform powered by artificial intelligence that can quickly create original music. It uses complex machine learning models and neural network technology to analyze patterns and structures from millions of songs, producing high-quality melodies, harmonies, and vocals. The main advantage of this product is its ability to accelerate music creation, support customization across various genres and styles, and offer flexible generation options. It is ideal for music creators, content producers, and business users, helping them save time, inspire creativity, and generate music tailored to specific needs. The product offers a free trial and various paid plans to meet different user requirements.

API.box is a platform offering advanced AI interfaces designed to help developers quickly integrate AI capabilities into their projects. It provides comprehensive API documentation and detailed invocation logs, ensuring efficient development and stable system performance. With enterprise-level security and robust scalability, it supports high concurrency demands while offering a free trial and licensed outputs for commercial use, making it an ideal choice for developers and businesses.

RapBank is a dataset focused on rap music, collecting a large number of rap songs from YouTube and offering a meticulously designed data preprocessing workflow. This dataset is significant for the field of music generation as it provides a wealth of rap music content that can be used for training and testing music generation models. The RapBank dataset includes 94,164 song links, successfully downloaded 92,371 songs, totaling 5,586 hours of music, covering 84 different languages, with English songs accounting for the majority, approximately two-thirds of the total duration.

SunoAiFree is a cutting-edge AI music generation platform focused on transforming text into music. It offers free AI music generation services, enabling users to swiftly create high-quality music tracks that meet industry standards. SunoAiFree features advanced technology, supports various language inputs, comprehends, and generates corresponding music with rapid generation speed and high-quality output, catering to the needs of diverse users.

The Free AI Song Generator is an online tool that uses artificial intelligence to create personalized songs based on user input. It combines melody, harmony, and rhythm to generate complete songs. Background information about the product indicates that this tool has been trusted by over 25,000 musicians, content creators, and music enthusiasts worldwide. It offers free music creation services without subscription requirements, supports various music styles, and allows users to commercially use the generated songs.

Aimi Sync is an online application that allows users to easily synchronize customized, generative music with their videos. The music is 100% copyright clear and royalty-free. The main advantages of the product include automated music scoring, creative control, a diverse range of music types, and narration generation in multiple languages and voices, allowing content to reach a broader audience. Aimi Sync aims to streamline the video production process, enhance efficiency, and ensure that copyright issues related to music and narration are properly addressed. The product currently offers a free trial.

MelodyFlow is a high-fidelity music generation and editing model based on text control. It utilizes continuous latent representation sequences to avoid information loss associated with discrete representations. Built on a diffusion transformer architecture and trained with flow matching objectives, the model can generate and edit a diverse range of high-quality stereo samples while maintaining the simplicity of text descriptions. MelodyFlow also explores a novel regularized latent inversion method for text-guided editing in zero-shot testing, demonstrating its superior performance across various music editing prompts. The model has been evaluated using objective and subjective metrics, confirming that it matches the quality and efficiency of established benchmarks in standard text-to-music evaluations while surpassing previous state-of-the-art techniques in music editing.

SoundStorm is an audio generation technology developed by Google Research that significantly reduces the time needed for audio synthesis by generating audio tokens in parallel. This technology can produce high-quality audio that maintains high consistency with speech and acoustic conditions, and can be integrated with text-to-semantic models to control the speech content, speaker voice, and speaking turns, facilitating long-text speech synthesis and the generation of natural dialogues. The significance of SoundStorm lies in its ability to tackle the slow inference speed issues faced by traditional autoregressive audio generation models when processing long sequences, thereby enhancing both the efficiency and quality of audio generation.

Audio Muse is a comprehensive online audio processing platform that meets all your audio needs, featuring a wide array of easily accessible tools. This product is popular among music lovers and creators for its user-friendliness, multifunctionality, and AI music creation capabilities. It allows users to create unique background music online, choose from various music styles, themes, and moods, and leverage artificial intelligence to generate infinite music possibilities. Background information indicates that 1.4K music enthusiasts have come together here, with 1K creators generating over 1.5K musical tracks.

MuVi is an innovative framework that analyzes video content to extract contextually and temporally relevant features, generating music that aligns with the mood, theme, rhythm, and tempo of the video. This framework implements a comparative music-visual pre-training scheme to ensure the periodic synchronization of musical phrases, and showcases the capabilities of a flow-matching-based music generator with contextual learning, allowing for control over the style and type of generated music. MuVi demonstrates superior performance in audio quality and temporal synchronization, providing new solutions for the integration of audio and video content and enhancing immersive experiences.

UniMuMo is a multimodal model capable of taking any text, music, and motion data as input conditions to generate outputs across all three modalities. The model bridges these modalities by converting music, motion, and text into token-based representations through a unified encoder-decoder architecture. By fine-tuning existing pretrained unimodal models, it significantly reduces computational requirements. UniMuMo has achieved competitive results in all unidirectional generation benchmarks across music, motion, and text modalities.

QA-MDT is an open-source music generation model that integrates state-of-the-art models for music creation. It is based on various open-source projects, including AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. The QA-MDT model can generate high-quality music by utilizing diverse training strategies. It is particularly suitable for researchers and developers interested in music generation.

OpenMusic is an AI-based music creation model that utilizes deep learning technology to generate new musical works based on user input or music fragments. This model holds revolutionary significance in the field of music production and composition by lowering the barriers to music creation, enabling individuals without a musical background to compose beautiful music.

Seed-Music is a music generation system that supports the creation of expressive multilingual vocal music within a unified framework, allowing for precise note-level adjustments and the integration of users' voices into music compositions. The system employs advanced language models and diffusion models, providing diverse creative tools to meet various music production needs.

DogMusic AI is a tool that utilizes advanced AI technology to create personalized relaxation music for pet dogs. By analyzing dogs' preferences, it quickly generates tailored music to help dogs remain calm and happy. Product background indicates that 185 users are currently using DogMusic AI, and a 40% discount is currently available for the first 60 customers.

FluxMusic is a text-to-music generation model implemented in PyTorch that explores a straightforward method for generating music from text prompts using a diffusion-based flow transformer. This model can create music segments based on textual cues, showcasing both innovation and technical complexity. It represents cutting-edge technology in the field of music generation, offering new possibilities for musical creativity.

FaceTune.ai is an intelligent application that combines facial emotion recognition technology with personalized music experiences. By analyzing users' facial expressions in real-time, it generates or recommends music that corresponds to their emotions, providing an immersive musical experience. The product is under development and includes features such as facial emotion recognition, gamification elements, personalized music experiences, and music API integration, all aimed at enhancing users' enjoyment of music through technology.

Stable Audio ControlNet is a music generation model based on Stable Audio Open, fine-tuned with DiT ControlNet. It can operate on GPUs with 16GB VRAM and supports audio control. Although still in development, it is capable of generating and controlling music, offering significant technical implications and application potential.

JASCO is a text-to-music generation model that combines symbolic and audio-based conditioning. It can generate high-quality music samples based on global text descriptions and fine-grained local controls. Built upon the stream matching modeling paradigm and a novel conditioning method, JASCO allows music generation to be controlled simultaneously by both local (e.g., chord) and global (text description) cues. By utilizing information bottleneck layers and temporal blurring, it extracts information relevant to specific controls, enabling the combination of symbolic and audio-based conditioning within the same text-to-music model.

Woy.ai is an AI tool directory providing a curated list of the latest AI tools for 2024. It serves as a platform for tech enthusiasts, developers, and businesses to discover and utilize cutting-edge advancements in artificial intelligence.

Zona is an application that leverages artificial intelligence to generate music. It can transform your ideas into musical pieces without requiring any musical expertise. With Zona, you can effortlessly create your own songs and share them with the world. It dismantles the barriers to music creation, allowing your musical dreams to become a reality.