compute mfcc for varying time intervals based on time stamps

问题

I came across this nice tutorial https://github.com/manashmndl/DeadSimpleSpeechRecognizer where the data is trained based on samples separated by folders and all mfcc are calculated at once.

I am trying to achieve something similar but in a different way.

Based on this : https://librosa.github.io/librosa/generated/librosa.feature.mfcc.html

librosa can compute mfcc for any audio. as follows :

import librosa  
y, sr = librosa.load('test.wav')
mymfcc= librosa.feature.mfcc(y=y, sr =sr)

but I want to calculate mfcc for the audio part by part based on timestamps from a file.

the file has labels and timestamps as follows :

0.0 2.0 sound1
2.0 4.0 sound2
4.0 7.0 silence
7.0 11.0 sound1

I want to calculate mfcc of each range, my hope is to arrive at a labelled train data that looks like mfcc and its corresponding label. mfcc_1 , sound1 mfcc_2, sound2
and so on.

How do I achieve this?

I looked at generate mfcc's for audio segments based on annotated file , and question is similar but I found both the question and answer somewhat hard to follow (because I'm very new to this field).

TIA

UPDATE: My Code :

import librosa
from subprocess import call

def ListDir():
    call(["ls", "-l"])

def main():
    ListDir()
    readfile_return_segmentsmfcc()

my_segments =[]
# reading annotated file
def         readfile_return_segmentsmfcc():

    pat ='000.mp3'
    y, sr = librosa.load(pat)

    print "\n sample rate :"
    print sr

    with open("000.txt", "rb") as f:
        for line in f.readlines():
            start_time, end_time, label = line.split('\t')
            start_time = float(start_time)
            end_time = float(end_time)
            label = label.strip()
            my_segments.append((start_time, end_time, label))

            start_index = librosa.time_to_samples(start_time)
            end_index = librosa.time_to_samples(end_time)

            required_slice = y[start_index:end_index]
            required_mfcc = librosa.feature.mfcc(y=required_slice, sr=sr)
            print "Mfcc size is {} ".format(mfcc.shape)


            print start,end,label


    return my_segments


main()

回答1:

read the start and end times:
start=2.0 end=4.0
convert to samples index using librosa.time_to_samples:
start_index = librosa.time_to_samples(start)
end_index = librosa.time_to_samples(end)
use python [:] operator to get the relevant slice from data:
slice = y[int(start_index):int(end_index)]
compute mfcc on slice, etc.

来源：https://stackoverflow.com/questions/48513824/compute-mfcc-for-varying-time-intervals-based-on-time-stamps

标签

python

audio

mfcc

librosa