This is an official implemetation of Spatial Voice Conversion: Voice Conversion Preserving Spatial Information and Non-target Signals.

Traditional voice conversion (VC) focuses on single-channel audio and ignores background noise signals. In contrast, Spatial Voice Conversion (Spatial VC) is a new voice conversion task that performs voice conversion on multi-channel signals while preserving spatial information and non-target signals. This task aims to provide a more immersive and realistic auditory experience in augmented reality and virtual reality.

This repository offers a baseline for Spatial VC using an approach that combines blind source separation, voice conversion, and spatial mixing, as illustrated below.

You can access the demo page from here.

You can install the required Python packages with the following command:

pip3 install -r requirements.txt

You need to train the Voice Conversion (VC) model. Move to the VC/DDSP-SVC directory and follow the instructions in the README to proceed with the training.

You can try Spatial VC using the command python3 experiment.py. The results will be output under the output/test directory.