CODEWITHSUNDEEP
pythonnumpysignal-processingspectrogramlibrosa
ignoring_gravity
ignoring_gravity

Reputation: 10476

Shape of librosa.feature.melspectrogram

I'm trying to understand the output of librosa.feature.melspectrogram:

>>> import numpy as np
>>> from librosa.feature import melspectrogram
>>>
>>>
>>> melspectrogram(np.random.randn(128), n_mels=128).shape
(128, 1)
>>> melspectrogram(np.random.randn(900), n_mels=128).shape
(128, 2)
>>> melspectrogram(np.random.randn(500), n_mels=128).shape
(128, 1)
>>> melspectrogram(np.random.randn(512), n_mels=128).shape
(128, 2)
>>> melspectrogram(np.random.randn(511), n_mels=128).shape
(128, 1)
>>> melspectrogram(np.random.randn(1023), n_mels=128).shape
(128, 2)
>>> melspectrogram(np.random.randn(1024), n_mels=128).shape
(128, 3)
>>> melspectrogram(np.random.randn(2055), n_mels=128).shape
(128, 5)
>>> melspectrogram(np.random.randn(2047), n_mels=128).shape
(128, 4)

What determines the second value of its shape? The first one is clear, it's n_mels, but from the docs I can't understand where the second one comes from.

Upvotes: 2

Views: 1865

Answers (1)

Hendrik
Hendrik

Reputation: 5310

It's the length of the signal in frames (not samples), depending on window and hop length. See this answer.

Concretely: 1 + len(y) // hop_length

Upvotes: 2

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