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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 SlidingWindowFeature (pyannote.core.feature.SlidingWindowFeature)
Step1:  SlidingWindowFeature are used to manage feature vectors extracted on a sliding window (e.g. MFCC in audio processing).
Step2:  Cropping
You may use crop to extract a temporal subset
Step3:  Need help?
You can always try the following...
Who knows? It might give you the information you are looking for!
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Python Code:
from pyannote.core import SlidingWindowFeature, SlidingWindow
Explanation: SlidingWindowFeature (pyannote.core.feature.SlidingWindowFeature)
End of explanation
# one 4-dimensional feature vector extracted every 100ms from a 200ms window
frame = SlidingWindow(start=0.0, step=0.100, duration=0.200)
# random for illustration purposes
data = np.random.randn(100, 4)
features = SlidingWindowFeature(data, frame)
Explanation: SlidingWindowFeature are used to manage feature vectors extracted on a sliding window (e.g. MFCC in audio processing).
End of explanation
help(features.crop)
from pyannote.core import Segment
features.crop(Segment(2, 3))
Explanation: Cropping
You may use crop to extract a temporal subset:
End of explanation
help(SlidingWindowFeature)
Explanation: Need help?
You can always try the following...
Who knows? It might give you the information you are looking for!
End of explanation
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