ACE Studio
ACE Studio is an AI-powered desktop application designed for music production, enabling users to create realistic singing vocals by inputting MIDI files and lyrics. The software utilizes advanced artificial intelligence and machine learning technologies to generate human-like vocal performances, offering a diverse selection of AI singers across various musical styles. Users can customize vocal characteristics such as pitch, vibrato, breath, emotion, and formant to achieve the desired sound. The platform supports importing MIDI files, adding lyrics, and crafting realistic vocal performances, with features like voice blending and controls for breath and emotion to tailor the output. ACE Studio's user-friendly interface is compatible with both touchscreen tablets and desktop computers and can be hosted on a secure government cloud or within a local data center, enabling field operations with confidence.
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Dreamtonics Synthesizer V
Warmth and tonality are hallmarks of the human singing voice. Behind the scenes, Synthesize V leverages a deep neural network-based synthesis engine capable of generating incredibly life-like singing voices. Plus, unlike other solutions that utilize neural networks, our first-of-its-kind synthesizer is 100% offline yet runs at lightning-fast speeds. Bad connection? No worries, you will never lose access to your work. Experiment with an expanding inventory of voices ready to plug and play with Synthesizer V Studio. Dive deeper and customize voices with dynamic vocal modes like chest, belt, and breathy. Visualize your modifications in waveforms in real-time via the live rendering feature, helping you minimize hearing fatigue and reduce the idea-to-sound cycle. Synthesizer V AI voices are available natively in English, Japanese and Chinese. Plus, the cross-lingual synthesis feature breaks the language barrier, empowering any voice to sing in any of our three languages!
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Seed-Music
Seed-Music is a unified framework for high-quality and controlled music generation and editing, capable of producing vocal and instrumental works from multimodal inputs such as lyrics, style descriptions, sheet music, audio references, or voice prompts, and of supporting post-production editing of existing tracks by allowing direct modification of melodies, timbres, lyrics, or instruments. It combines autoregressive language modeling with diffusion approaches and a three-stage pipeline comprising representation learning (which encodes raw audio into intermediate representations, including audio tokens, symbolic music tokens, and vocoder latents), generation (which transforms these multimodal inputs into music representations), and rendering (which converts those representations into high-fidelity audio). The system supports lead-sheet to song conversion, singing synthesis, voice conversion, audio continuation, style transfer, and fine-grained control over music structure.
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OpenAI Jukebox
We’re introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artistic styles. We’re releasing the model weights and code, along with a tool to explore the generated samples. Provided with genre, artist, and lyrics as input, Jukebox outputs a new music sample produced from scratch. Jukebox produces a wide range of music and singing styles and generalizes to lyrics not seen during training. All the lyrics below have been co-written by a language model and OpenAI researchers. When conditioned on lyrics seen during training, Jukebox produces songs very different from the original songs it was trained on. We provide 12 seconds of audio to condition on and Jukebox completes the rest in a specified style. We chose to work on music because we want to continue to push the boundaries of generative models. Jukebox’s autoencoder model compresses audio to a discrete space, using a quantization-based approach called VQ-VAE.
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