Update URLs and repository information

_pages/about.md

@@ -12,10 +12,10 @@ I’m a third-year PhD student in [UKRI Centre for Doctoral Training in Artifici
 My current PhD theme is about leveraging deep generative models and signal processing techniques for controllable and expressive voice synthesis.
 The projects I made for achieving this goal are:
 
-- [diffwave-sr](https://yoyololicon.github.io/diffwave-sr/): unsupervised speech super-resolution (bandwidth extension) using posterior sampling in diffusion models.
-- [duet-svs-diffusion](https://github.com/yoyololicon/duet-svs-diffusion): unsupervised duet singing voice separation using posterior sampling in diffusion models.
-- [golf](https://yoyololicon.github.io/golf-demo/): a light-weight neural voice synthesiser with glottal-flow models and differentiable time-varying linear prediction synthesis.
-- [torchlpc](https://github.com/DiffAPF/LA-2A): efficient implementation of differentiable time-varying linear prediction synthesis in PyTorch.
+- [diffwave-sr](https://iamycy.github.io/diffwave-sr/): unsupervised speech super-resolution (bandwidth extension) using posterior sampling in diffusion models.
+- [duet-svs-diffusion](https://github.com/iamycy/duet-svs-diffusion): unsupervised duet singing voice separation using posterior sampling in diffusion models.
+- [golf](https://iamycy.github.io/golf2-demo/): a light-weight neural voice synthesiser with glottal-flow models and differentiable time-varying linear prediction synthesis.
+- [torchlpc](https://github.com/DiffAPF/torchlpc): efficient implementation of differentiable time-varying linear prediction synthesis in PyTorch.
 
 Before I started my PhD, I was doing software engineering and working with [HTC](https://www.htc.com/) and [Rayark Inc.](https://www.rayark.com/).
 I do independent research in my spare time.
@@ -27,7 +27,7 @@ I love making contributions on GitHub. Some of my most starred projects are:
 - [torchnmf](https://pytorch-nmf.readthedocs.io/): a package that can help build complex NMF models.
 - [constant-memory-waveglow](https://zenodo.org/record/4353123): training waveglow with constant memory cost.
 - [variational-diffwave](https://github.com/yoyololicon/variational-diffwave): training DiffWave using unbiased ELBO.
-- [torchcomp](https://github.com/yoyololicon/torchlpc): efficient implementation of differentiable feed-forward compressor in PyTorch.
+- [torchcomp](https://github.com/DiffAPF/torchcomp): efficient implementation of differentiable feed-forward compressor in PyTorch.
 
 I'm also the main contributor to making [torchaudio.functional.lfilter](https://pytorch.org/audio/stable/functional.html#lfilter) differentiable.
 To know what I'm working on at the moment, you can check out my [Kanban](https://github.com/users/yoyololicon/projects/3/) on GitHub.