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Hi, I am trying to get the MFCC features from a sample .wav audio file, but my output doesn't match the one from LibRosa library in python(this is critical as my CoreML model is trained with LibRosa's…
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I analyzed speaker_diarization and I noticed something that makes me wonder.
Why predictions from knn_speaker_10 and knn_speaker_male_female are not used in clustering?
K-means use only part of fe…
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Hi,
This repo is a great inspiration and guide for audio processing for ML models, but few functionalities like first and second derivatives (delta 1 and delta 2) of mfcc features are missing which …
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english_mfcc = np.array([]).reshape(0, num_mfcc_features)
for file in glob.glob(codePath + 'english/*.npy'):
at this line you used .npy what this mean can u share it and tell how u created it.
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Hello, I'm currently working on my thesis about music genre classification using the FMA dataset. However, I'm having trouble understanding the meaning of these columns labeled `01`, `02`, `03`, and s…
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Hello,
First of all, thank you for providing a great library.
I would like to process a signal of 0.1 seconds (1600) for short-term features.
```python
F, f_names = ShortTermFeatures.feature_ext…
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In the paper, one of the acoustic features is referred to as "mel-cepstral coefficients" (MCC). Is this the same as "mel-frequency cepstral coeffiencts" (MFCC)? If yes, I would suggest that authors me…
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`smile = opensmile.Smile(feature_set=opensmile.FeatureSet.eGeMAPSv01b, feature_level=opensmile.FeatureLevel.Functionals)`
The above script gives me features with shape `1x88`, but I want frame-wise…
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I want to get the features from prosody(3-features), eGeMAPS(23-features), and MFCC(39-features) stored in a single CSV with a timestamp.