Search Results for author:
Found 7 papers, 4 papers with code
SingSong: Generating musical accompaniments from singing
We present SingSong, a system that generates instrumental music to accompany input vocals, potentially offering musicians and non-musicians alike an intuitive new way to create music featuring their own voice.
MusicLM: Generating Music From Text
We introduce MusicLM, a model generating high-fidelity music from text descriptions such as "a calming violin melody backed by a distorted guitar riff".
Ranked #8 on
Text-to-Music Generation
on MusicCaps
Streamable Neural Audio Synthesis With Non-Causal Convolutions
As our method is based on a post-training reconfiguration of the model, we show that it is able to transform models trained without causal constraints into a streaming model.
RAVE: A variational autoencoder for fast and high-quality neural audio synthesis
By leveraging a multi-band decomposition of the raw waveform, we show that our model is the first able to generate 48kHz audio signals, while simultaneously running 20 times faster than real-time on a standard laptop CPU.
Timbre latent space: exploration and creative aspects
Recent studies show the ability of unsupervised models to learn invertible audio representations using Auto-Encoders.
Diet deep generative audio models with structured lottery
This hypothesis states that extremely efficient small sub-networks exist in deep models and would provide higher accuracy than larger models if trained in isolation.
Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders
Its training data subsets can directly be visualized in the 3D latent representation.
