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I want to thank all the authors for the great work that they have done with this paper.
I am trying to reproduce the Librispeech model training to get a better sense of how the model is training i…
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# Supervised audio separation
### [U-Net on STFT](https://research.atspotify.com/publications/singing-voice-separation-with-deep-u-net-convolutional-networks/) (Jansson 17')
### [Wave UNet](https://…
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Hi!
Did you observe trainings with different sampling rates such as 8K->16K, 8K-> 22K, 16K->22K, etc.. ?
(diferent from [demo page](https://mindslab-ai.github.io/nuwave/))
and what changes shou…
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I would like to train the network if I use 16k sample rate audio, and require a frame length of 32ms and a frame shift of 16ms. How should I modify the parameters in the preprocessing, thank you for y…
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[Full-Band LPCNet: A Real-Time Neural Vocoder for 48 kHz Audio With a CPU](https://xploreqa.ieee.org/document/9455356/)
GPU is expensive and power-hungry.
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Running the codec with full-band input (48 khz sr):
bazel-bin/encoder_main --input_path=path/to/fullband-audio/*.wav --output_dir= dir/to/bs_output --bitrate=6000
bazel-bin/decoder_main --encoded_…
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Have trained `update_v2` branch on :
* Extracted Semantic token from HuBert Large layer 16 with 1024 cluster Kmean. (`50 tok/sec`)
* Extracted Acoustic token from Encodec 24 khz sample rate, 240 ho…
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Hello All,
Have a question on GPU Resource Requirement for a Training Project I am doing with Piper.
Following the Training Guide and the video by Thorsten Müller.
Data: Single Speaker, 18,000 …
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In the white paper, they mention conditioning to a particular speaker as an input they condition globally, and the TTS component as an up-sampled (deconvolution) conditioned locally. For the latter, t…
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I'm doing some tests for CPU and GPU environment usages for prediction (Predict.py).
I'm using an audio file `Audio: mp3, 44100 Hz, stereo, fltp, 192 kb/s` of duration `00:03:15.29`
```sh
$ ffpro…