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Beyond 20 words, it seems to talk a blue streak.
Below 10, it produces pauses and inhumanly noises.
I've tried padding the short sentences with words consisting of the single letter "s" and then subtracting int(0.25 * Synthesizer.sample_rate) * padding_size from the b_ends array. It works, but only to an extent (sometimes it cuts too much, sometimes it leaves in a bit of the padding).
Is there any better way to teach the synth to process shorter sentences?
The text was updated successfully, but these errors were encountered:
Poor performance on short inputs results from bad training data. You can try the alternative model in #538 and see if it gets better.
Problems with long inputs are caused by a failure of the attention mechanism. Solution is to implement a better one and retrain the model. Much easier said than done.
Thank you so much! The alternative model does get the short sentences right (also gets rid of weird pauses).
Re the long ones--I've got a working method of handling them (basically considering them in chunks of 20 words and seeing if I can split on commas).
Beyond 20 words, it seems to talk a blue streak.
Below 10, it produces pauses and inhumanly noises.
I've tried padding the short sentences with words consisting of the single letter "s" and then subtracting int(0.25 * Synthesizer.sample_rate) * padding_size from the b_ends array. It works, but only to an extent (sometimes it cuts too much, sometimes it leaves in a bit of the padding).
Is there any better way to teach the synth to process shorter sentences?
The text was updated successfully, but these errors were encountered: