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Hi, I try exporting the process of feature extraction to onnx:
```
import torch
import torchaudio
model = torchaudio.transforms.MelSpectrogram()
x = torch.randn(1, 16000)
torch.onnx.export(mod…
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I am trying to implement the open model using the onnx files provided.
The output of the embedding_model.onnx is (1,1,1,96)
It's input is (from [here](https://github.com/dscripka/openWakeWord/blob…
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The origin API was
```
static std::vector melspectrogram(
std::vector &x, int sr, int n_fft, int n_hop,
const std::string &win, bool center, const std::string &mode, float power,
…
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https://pytorch.org/audio/transforms.html?highlight=melspectrogram#torchaudio.transforms.MelSpectrogram:
```
torchaudio.transforms.MelSpectrogram(sample_rate=16000, n_fft=400, win_length=None, hop_l…
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Is there any function which creates the mel-scaled spectrogram? There is a functionality in librosa librosa.feature.melspectrogram(), is there any similar method in .js?
Thank you
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In the inference square of the [collab notebook ](https://colab.research.google.com/notebooks/magenta/onsets_frames_transcription/onsets_frames_transcription.ipynb), I get the following error:
```…
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Colab Notebook example cannot be run
error message:
`Using cuda for inference.
Reading video frames...
Number of frames available for inference: 210
Traceback (most recent call last):
File "/c…
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Number of frames available for inference: 373
Traceback (most recent call last):
File "inference.py", line 280, in
main()
File "inference.py", line 225, in main
mel = audio.melspectr…
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I tried to make a new feature extractor (features/melspectrogram.py) and experienced some issues solved. Just post them here in case it could be helpful to other new beginners.
Similar to features/…
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I am facing following issue (attached the screen shot) while running detection_from_microphone.py with the give pre-trained model available in the folder docs/models/alexa.md
Using the following c…