Commit 53f420ec authored by LiniEisha's avatar LiniEisha

Reformatting noise.py

parent 12d23d82
......@@ -10,18 +10,18 @@ def read_file(file_name):
sample_path = sample_directory + sample_file
# generating audio time series and a sampling rate (int)
y, sr = librosa.load(sample_path)
a, sr = librosa.load(sample_path)
return y, sr
return a, sr
'''MFCC'''
def mffc_highshelf(y, sr):
def mffc_highshelf(a, sr):
mfcc = python_speech_features.base.mfcc(y)
mfcc = python_speech_features.base.logfbank(y)
mfcc = python_speech_features.base.mfcc(a)
mfcc = python_speech_features.base.logfbank(a)
mfcc = python_speech_features.base.lifter(mfcc)
sum_of_squares = []
......@@ -39,22 +39,22 @@ def mffc_highshelf(y, sr):
min_hz = min(hz)
speech_booster = AudioEffectsChain().highshelf(frequency=min_hz*(-1)*1.2, gain=-12.0, slope=0.6).limiter(gain=8.0)
y_speach_boosted = speech_booster(y)
a_speach_boosted = speech_booster(a)
return (y_speach_boosted)
return (a_speach_boosted)
def mfcc_lowshelf(y, sr):
def mfcc_lowshelf(a, sr):
mfcc = python_speech_features.base.mfcc(y)
mfcc = python_speech_features.base.logfbank(y)
mfcc = python_speech_features.base.mfcc(a)
mfcc = python_speech_features.base.logfbank(a)
mfcc = python_speech_features.base.lifter(mfcc)
sum_of_squares = []
index = -1
for r in mfcc:
for x in mfcc:
sum_of_squares.append(0)
index = index + 1
for n in r:
for n in x:
sum_of_squares[index] = sum_of_squares[index] + n**2
strongest_frame = sum_of_squares.index(max(sum_of_squares))
......@@ -64,49 +64,49 @@ def mfcc_lowshelf(y, sr):
min_hz = min(hz)
speech_booster = AudioEffectsChain().lowshelf(frequency=min_hz*(-1), gain=12.0, slope=0.5)
y_speach_boosted = speech_booster(y)
a_speach_boosted = speech_booster(a)
return (y_speach_boosted)
return (a_speach_boosted)
def trim_silence(y):
y_trimmed, index = librosa.effects.trim(y, top_db=20, frame_length=2, hop_length=500)
trimmed_length = librosa.get_duration(y) - librosa.get_duration(y_trimmed)
a_trimmed, index = librosa.effects.trim(y, top_db=20, frame_length=2, hop_length=500)
trimmed_length = librosa.get_duration(y) - librosa.get_duration(a_trimmed)
return y_trimmed, trimmed_length
return a_trimmed, trimmed_length
def enhance(y):
apply_audio_effects = AudioEffectsChain().lowshelf(gain=10.0, frequency=260, slope=0.1).reverb(reverberance=25, hf_damping=5, room_scale=5, stereo_depth=50, pre_delay=20, wet_gain=0, wet_only=False)#.normalize()
y_enhanced = apply_audio_effects(y)
a_enhanced = apply_audio_effects(y)
return y_enhanced
return a_enhanced
def output_file(destination ,filename, y, sr, ext=""):
def output_file(destination ,filename, a, sr, ext=""):
destination = destination + filename[:-4] + ext + '.wav'
librosa.output.write_wav(destination, y, sr)
librosa.output.write_wav(destination, a, sr)
lectures = ['Lecture01.wav']
for s in lectures:
filename = s
y, sr = read_file(filename)
a, sr = read_file(filename)
# y_reduced_centroid_s = reduce_noise_centroid_s(y, sr)
y_reduced_mfcc_lowshelf = mfcc_lowshelf(y, sr)
y_reduced_mfcc_highshelf = mffc_highshelf(y, sr)
# a_reduced_centroid_s = reduce_noise_centroid_s(a, sr)
a_reduced_mfcc_lowshelf = mfcc_lowshelf(a, sr)
a_reduced_mfcc_highshelf = mffc_highshelf(a, sr)
# trimming silences
# y_reduced_centroid_s, time_trimmed = trim_silence(y_reduced_centroid_s)
y_reduced_mfcc_up, time_trimmed = trim_silence(mfcc_lowshelf)
y_reduced_mfcc_down, time_trimmed = trim_silence(mffc_highshelf)
# a_reduced_centroid_s, time_trimmed = trim_silence(a_reduced_centroid_s)
a_reduced_mfcc_up, time_trimmed = trim_silence(mfcc_lowshelf)
a_reduced_mfcc_down, time_trimmed = trim_silence(mffc_highshelf)
# output_file('lectures_trimmed_noise_reduced/' ,filename, y_reduced_centroid_s, sr, '_ctr_s')
output_file('lectures_trimmed_noise_reduced/' ,filename, y_reduced_mfcc_up, sr, '_mfcc_up')
# output_file('lectures_trimmed_noise_reduced/' ,filename, y_reduced_mfcc_down, sr, '_mfcc_down')
# output_file('lectures_trimmed_noise_reduced/' ,filename, y, sr, '_org')
output_file('lectures_trimmed_noise_reduced/' ,filename, a_reduced_mfcc_up, sr, '_mfcc_up')
# output_file('lectures_trimmed_noise_reduced/' ,filename, a_reduced_mfcc_down, sr, '_mfcc_down')
# output_file('lectures_trimmed_noise_reduced/' ,filename, a, sr, '_org')
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