Rishikesh (ऋषिकेश)

Yes Greedy is not enough, because this task is many to many conversions which is quite hectic for single run greedy solutions. My training loss is around 5 (ideally loss...

@bharani-y Teacher training set is a knowledge distillation method which called teacher student learning, where we are training a large Teacher model to learn probability distribution of the complex data,...

> PS. I dived into some of the NAR (non-autoregressive) machine translation papers and the consensus was that training a NAR model (and they use even more "tricks" than SoundStorm)...

@bharani-y are you same `dataloader` and `variable random window` as in my repo ? Also which semantic tokenizer you are using and how many clusters in your semantic dataset ?

Currently I am training model on Large Libri-TTS dataset from here : https://huggingface.co/datasets/collabora/whisperspeech/tree/main

> From my experiment I confirm that just doing some very naive semantic tokens upsampling using hubert (50hz) to match encodec (75hz) works, can get some reasonable voices. My own...

> below I provide the core code and one sample, which I think is very close to the paper's description > https://github.com/feng-yufei/shared_debugging_code/blob/main/soundstorm.py, hope it can be useful @feng-yufei sample is...

> For experiment on larger dataset I tried LibriTTS 100/360/500 merged together, the quality is strangely bad.(50% top 10 training accuracy while LJspeech has 65%). I have also trained on...

@p0p4k sample sounds good, I think with more training it will getting lot better. I think multi-linguility is easy to implement in this repo. I think problem occurs when you...

Currently facing this issue : ``` run.sh: line 37: utils/parse_options.sh: No such file or directory Prepare LibriTTS dataset split the data for 1 GPUs cat: data/val/wav.scp: No such file or...