Incorrect segregation of voiced and unvoiced segments

[tumul-80]

Hello,

I will like to get the voiced segments from any audio file ( .wav format) and plot it against the time series of the original audio. I modified your code a bit and ran it on a simple audio file. For instance, I recorded a simple audio file with just my voice and tried to find voiced segments, but the code mistakenly gets voiced segments and classifies most of actual human voice as "Unvoiced segments"

What should I do?

audio_data, sampling_rate = librosa.load('try_voice.wav')
plt.figure(figsize=(14, 5))
librosa.display.waveplot(audio_data, sr=sampling_rate)

vad=wb.Vad()
filename= 'try_voice.wav'
audio= audiosegment.from_file(filename)

seg = audio.resample(sample_rate_Hz=32000, sample_width=2, channels=1)
results = seg.detect_voice()
voiced = [tup[1] for tup in results if tup[0] == 'v']
unvoiced = [tup[1] for tup in results if tup[0] == 'u']

voiced_segment = voiced[0].reduce(voiced[1:])
voiced_segment.export("voiced.wav", format="WAV")
voiced, sampling_rate_v= librosa.load('voiced.wav')

duration = len(voiced)/sampling_rate_v
time = np.arange(0,duration,1/sampling_rate_v) #time vector
plt.figure()
librosa.display.waveplot(voiced, sr=sampling_rate_v)
plt.show()