Binaural Speech Synthesis

Related tags

Text Data & NLPBinauralSpeechSynthesis
Overview

Binaural Speech Synthesis

This repository contains code to train a mono-to-binaural neural sound renderer. If you use this code or the provided dataset, please cite our paper "Neural Synthesis of Binaural Speech from Mono Audio",

@inproceedings{richard2021binaural,
  title={Neural Synthesis of Binaural Speech from Mono Audio},
  author={Richard, Alexander and Markovic, Dejan and Gebru, Israel D and Krenn, Steven and Butler, Gladstone and de la Torre, Fernando and Sheikh, Yaser},
  booktitle={International Conference on Learning Representations},
  year={2021}
}

Code

Detailed instructions how to use the code will be release prior to ICLR 2021.

Dataset

The dataset will be released prior to ICLR 2021.

License

The code and dataset are release under CC-NC 4.0 International license.

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Comments
  • UserWarning: stft will soon require the return_complex parameter be given for real inputs

    UserWarning: stft will soon require the return_complex parameter be given for real inputs

    Hello,when I run the train.py, there is always a warning:

    UserWarning: stft will soon require the return_complex parameter be given for real inputs, and will further require that return_complex=True in a future PyTorch release. (Triggered internally at /pytorch/aten/src/ATen/native/SpectralOps.cpp:639.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore

    then nothing else.

    Could you help me solve it?

    opened by yijingshihenxiule 7
  • about the coordinate system and the pretrained network

    about the coordinate system and the pretrained network

    Hi, thanks for you great work!

    Since I am a beginner in and Audio and 3D, if you don't mind, I have some questions (that might be evident for you):

    You said that

    Receiver positions are therefore the same at all times. The tranmitter is the in the origin of the coordinate system and, from the receiver's perspective, x points forward, y points right, and z points up. <

    I took a look at the dataset, I guess that rx_positions is the positions of the receiver and tx_positions is the positions of the sound transmitter. If the origin of the coordinate system is in the transmitter, then why rx_positions are all zeros in (x,y,z) ?

    My another question is about the network, will you release the pretrained model? If not, can the provided training code produce similar outstanding results?

    And how the network generalizes, like for example, what if I change the mono-audio and the positions during inference? I have monoaudio and 3d positions of my own but I cannot finetune the model because I dont have ground-truth binaural audio.

    Thanks for your reply and again great work!

    opened by yihongXU 0
  • Adding Code of Conduct file

    Adding Code of Conduct file

    This is pull request was created automatically because we noticed your project was missing a Code of Conduct file.

    Code of Conduct files facilitate respectful and constructive communities by establishing expected behaviors for project contributors.

    This PR was crafted with love by Facebook's Open Source Team.

    CLA Signed 
    opened by facebook-github-bot 0
  • Adding Contributing file

    Adding Contributing file

    This is pull request was created automatically because we noticed your project was missing a Contributing file.

    CONTRIBUTING files explain how a developer can contribute to the project - which you should actively encourage.

    This PR was crafted with love by Facebook's Open Source Team.

    CLA Signed 
    opened by facebook-github-bot 0
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