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# machine-learning
  • c
    now this is the sex
  • c
    its getting there
  • h
    it's for when you train your model with arpabet (pronunciation betterizer)
  • c
    since i made up a new naming scheme i can tell which models have which batch size and lr
  • c
    (and if they have arpa or not)
  • h
    How am I supposed to update a model I’ve already made using Tacotron 2?
  • c
    retrain it and submit it
  • c
    i think i asked mr bean if you could do transfer learning with an updated dataset and he told me it was better off just retraining it from ljs
  • u
    zamn
  • c
    i need to know what clip this is and why that funny line happens
  • c
    this model is going to LOOSE ATTENTION
  • u
    retraining noel talknet melspec
  • u
    i think the hifigan is still gonna work despite the slightly different dataset
  • c
    I've noticed some voices sounds really robotic on colab but at uberduck they're better, why is that?
  • c
    It's the same hifigan generator
  • b
    probably because on uberduck most voices are (if i remember correctly) given the spongebob hifigan unless one is specifically trained for that model (or taken from the talknet if that character also has a talknet)
  • c
    Like I've said, it's the same generator
  • c
    I think it's some kind of processing in the hifigan part
  • b
    well spongebob's hifigan is high quality
  • i
    nah most models dont use the spongebob hifigan (wish they did its pretty solid)
  • b
    oh
  • b
    i thought they did :(
  • b
    anyways, im assuming his is better than the "universal" model in the notebook
  • u
    by default its the alex trebek hifigan
  • u
    on uber
  • u
    colab notebook hifigan is lj im pretty sure
  • b
    oh
  • c
    Yes
  • c
    The thing is, I finetuned a hifigan, tried to synthesize in colab, it sounds awful, in uberduck, with the same fine-tuned hifigan it sounds perfectly okay
  • u
    something tells me for one of those the hifigan was NOT applied
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