espnet VS StarGANv2-VC

You might check out this list from espnet. They list the different corpuses they use to train their models sorted by language and task (ASR, TTS etc):

https://github.com/espnet/espnet/blob/master/egs2/README.md

- https://github.com/espnet/espnet

This link has instructions for doing this for a Japanese model. It would have to be altered to work with ljspeech and the fine tune dataset.

This work is made possible by the excellent advancements in text to speech modeling. ESPnet is a great project and should be checked out for more advanced and a wider range of use cases. This pipeline was also made possible by the great work from espnet_onnx in building a framework to export models to ONNX.

CMU WavLab has ESPNet https://espnet.github.io/espnet/ which includes a number of high quality TTS models including VITS (which in my subjective experience is just as good as what is demonstrated here). Also the inference on various ESPNet pretrained TTS models is reasonable and sentences take on average 5 seconds per word to generate the waveform on my totally mid PC setup.

The reason I'm saying this is to point out that having and in-depth knowledge on speech processing/generation requires a lot of information about signal processing and human speech in general (eg. acoustics and phonetics). However, if you're not into learning everything there is to know about a subject, just take one state-of-the-art example and study that as best as you can. Pick one environment/toolkit, for example espnet and simply go with that.

https://github.com/espnet/espnet (kind of like a newer Kaldi, but also not beginner friendly)

both provide e2e ASR support but espnet does have more utilities where as speechbarain is clean

This is relatively small amount of speech to train the model from scratch, but you can train using another pre-trained model for initialization. There are numbers of end-to-end ASR toolkits which can be used for this: https://github.com/NVIDIA/NeMo and https://github.com/espnet/espnet

So far I've only been able to find StarGANv2. Which one redditor used to create this. Is this the best there is or are there better alternatives?

I used this to make this

This looks like it was previously known as Vocodes, made by echelon who is here on HN:

https://news.ycombinator.com/item?id=23965787

The code repos used are listed in their credits section, and it looks like a mixture of (customised?) Tacotron2, Glow-TTS, HifGan, and others. Videos are generated using Wav2Lip.

Text-To-Speech (TTS) has improved greatly over the past several years, but there's still a lot of metallic sounds in "pure" TTS implementations. I've started exploring voice style conversion, otherwise known as "voice cloning", and there are some interesting repos out there with decent results. These work differently from TTS, in that you don't type out the text to be spoken, but rather pass in an audio file of what you want the cloned speaker to say, and the system outputs an audio file with the same sounds (words, intonation) but with a different speaker identity.

This may be easier to get the right cadence and emotion in the generated audio, as text doesn't capture proper emotion and intonation. I suspect game character audio will use more of voice-style conversion instead of pure TTS simply to get the right emotional cadence of the lines being delivered.

Some interesting voice style conversion repos (in no order, just a random selection if anyone is interested in exploring):

https://github.com/yl4579/StarGANv2-VC