Comments (7)
andimarafioti
commented on August 17, 2024
tf.decode_raw doesn't support complex data (as in 3+2j) so that should be handled in some way: (https://www.tensorflow.org/versions/r1.4/api_docs/python/tf/decode_raw). Easiest way is to take the real and the imaginary part as two separate float32 vectors and make tfReader reunite them into complex64 values. Do you think that's a good idea?
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nperraud
commented on August 17, 2024
Well it will be simply two channels, one for real and one for imaginary, i.e no complex number.
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nperraud
commented on August 17, 2024
Sorry this is the first thing to do.
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andimarafioti
commented on August 17, 2024
Like this? https://github.com/andimarafioti/audioContextEncoder/blob/master/utils/tfReaderForStftCoeffs.py
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nperraud
commented on August 17, 2024
Probably. Did you also make the file to produce the tfReader file?
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nperraud
commented on August 17, 2024
Is this done?
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andimarafioti
commented on August 17, 2024
No, I'll address this in the fourth issue.
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Related Issues (17)
- Network that works with stft of signal without gap and targets stft of gap + sides HOT 18
- Network that works with stft of signal without gap and targets mag(stft) of gap + sides HOT 5
- Dataset pipeline HOT 1
- L2 loss and normalization
- Does more context improve the results? HOT 2
- This should be a parameter HOT 1
- update readme.md HOT 1
- No module named 'architecture' HOT 2
- network working with the STFT magnitude only HOT 71
- Network working with STFT real and imag HOT 8
- Re-organisation of the code HOT 2
- Nicki's hand crafted skip connection
- Use dropout correctly HOT 9
- Mag network with original phase HOT 4
- SNR on spectograms HOT 1
- Network that works with stft mag of signal without gap and targets stft mag of gap + sides HOT 1
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