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`phase_vocoder` currently accepts a single scalar parameter controlling the rate of time dilation. In principle, it shouldn't be difficult to either vectorize this, or support a slice+rate parameteri…
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Hi
this is a great work. I noticed that the ISTFT head does not use the same padding that you implemented, but uses the center padding which is provided by torch api according your config file.
for…
nukes updated
4 months ago
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“A PyTorch implementation of Robust Universal Neural Vocoding. Audio samples can be found here.“
The link you gave here is the sample you generated is the actual spectrum feed or the acoustic model…
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Thank you for open sourcing this great work!
One of the great advantages I see in vocoders operating in the time domain is how easy it is to combine the vocoding task with superresolution. You just…
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In case of vocoding one example, by folding the input example into batch of chunks, the inference can run faster.
https://github.com/pytorch/audio/blob/31dbb7540c78fe5d176948764cf9a20f55ac80dc/exam…
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Hi, I'm new to python and ML in general. I've got it to work on my mac m1, so that's nice. I've got the text to speech working but I was wondering: is it possible to learn a voice with a dataset and u…
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I tried two differenct versions of WaveRNN vocoders where each vocoder has different output node. The first one uses RAW (softmax 512-dim, 9-bit mu-law encoded waveform sample target) and last one use…
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In YTPs, it's common to use sped up and slowed down audio/video clips of the source. We could do the same thing, which would add variety to the output, especially for short carriers, and increase how …
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Hi, @haoheliu. Thank you for your awesome work.
1. After read code on the vocoder part, I found that there is only a pre-trained model and no training steps. Why is there no implementation of this …
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I am trying to integrate this model to tacotron 1 for TTS but since I do not have corresponding exact audios that are to be generated from the tacotron's output mel spectrogram, how should I go about …