Search Results for "lyrics"

HeartMuLa is the open-source library and reference implementation for the HeartMuLa family of music foundation models, designed to support both music generation and music-related understanding tasks in a cohesive stack. At the center is HeartMuLa, a music language model that generates music conditioned on inputs like lyrics and tags, with multilingual support that broadens the range of lyric-driven use cases. The project also includes HeartCodec, a music codec optimized for high reconstruction fidelity, enabling efficient tokenization and reconstruction workflows that are critical for training and generation pipelines. For text extraction from audio, it provides HeartTranscriptor, a Whisper-based model tuned specifically for lyrics transcription, which helps bridge generated or recorded audio back into structured text. ...

YuE is an open source project that provides a foundation model designed for full-song music generation using artificial intelligence. It focuses on transforming text inputs such as lyrics and genre prompts into complete musical compositions that include both vocal and instrumental tracks. Unlike many shorter audio generators, the model is capable of producing songs that last several minutes while maintaining coherent musical structure and alignment with the provided lyrics. YuE introduces a family of models built on large language model architectures that process music generation as a sequence prediction task. ...

...The project includes multiple model variants to meet different application needs, such as high-accuracy end-to-end interaction using an encoder-adapter-LLM framework and efficient real-time recognition using attention-based encoder-decoder architectures, giving developers flexibility in balancing performance and resource constraints. FireRedASR not only excels in traditional speech recognition tasks but also demonstrates strong capability in challenging scenarios like singing lyrics recognition, where accurate transcription is often difficult for conventional models.

Suno API is an unofficial open-source interface that enables developers to programmatically interact with Suno’s AI music generation platform, allowing automated creation of songs, lyrics, and audio content through API calls. It replicates the behavior of Suno’s web-based creation tools by reverse engineering internal endpoints and exposing them through a developer-friendly interface built with Python and FastAPI. The system supports asynchronous processing, enabling efficient handling of multiple generation requests and making it suitable for scalable applications and automation pipelines. ...

...Generating massive detailed textures, a la deepdream, fullHD/4K resolutions and above, various CLIP models (including multi-language from SBERT), continuous mode to process phrase lists (e.g. illustrating lyrics), pan/zoom motion with smooth interpolation. Direct RGB pixels optimization (very stable) depth-based 3D look (courtesy of deKxi, based on AdaBins), complex queries: text and/or image as main prompts, separate text prompts for style and to subtract (avoid) topics. Starting/resuming process from saved parameters or from an image.

...The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN training — and produces more realistic, expressive, and natural-sounding singing. The method introduces a “shallow diffusion” mechanism: instead of diffusing over many steps, generation begins at a shallow step determined adaptively, which leverages prior knowledge learned by a simple mel-spectrogram decoder and speeds up inference.

...CD+Graphics Scribe utility (separate download -- click "Browse All Files" above) can now convert existing CDG karaoke content to CMP (CD+Graphics Magic Project), LRC (Enhanced Lyrics), and ASS (Advanced SubStation Alpha) format.