def setUp(self):
"""
Generate one (short) frame of a 1 kHz sinusoid at a sampling
rate of 16 kHz. It doesn't matter too much what it is, just
that it is representative of some natural signal.
"""
self.pcm = ssp.PulseCodeModulation(16000)
self.seq = np.zeros(64)
p = self.pcm.seconds_to_period(1.0/1000);
for s in range(len(self.seq)):
self.seq[s] = np.sin(2*np.pi * s/p)
w = ssp.nuttall(len(self.seq)+1)
w = np.delete(w, -1)
self.seq = ssp.Window(self.seq, w)
def get_pitch(gen_path, basefilename):
(Fs, x) = io_wav.read(gen_path + basefilename + '.wav')
assert Fs == 16000
pcm = ssp.PulseCodeModulation(Fs)
frameSize = pcm.seconds_to_period(0.025, 'atleast') # 25ms Frame size
pitchSize = pcm.seconds_to_period(0.1, 'atmost') # 100ms Pitch size
pf = ssp.Frame(x, size=pitchSize, period=framePeriod)
pitch, ac = ssp.ACPitch(pf, pcm, loPitch,
hiPitch) # Initially pitch estimated
# Pre-emphasis
pre = ssp.parameter("Pre", None)
if pre is not None:
x = ssp.PoleFilter(x, pre) / 5
# Frame Splitting
f = ssp.Frame(x, size=frameSize, period=framePeriod)
# Windowing
aw = ssp.nuttall(frameSize + 1)
aw = np.delete(aw, -1)
w = ssp.Window(f, aw)
# Autocorrelation
ac = ssp.Autocorrelation(w)
if (len(ac) > len(pitch)):
d = len(ac) - len(pitch)
addon = np.ones(d) * pitch[-1]
pitch = np.hstack((pitch, addon))
# Save pitch as binary
lf0 = np.log(pitch)
lf0.astype('float32').tofile(gen_path + basefilename + '.lf0')
return pitch
# Timer
ti = time.clock()
def lap(func):
global ti
now = time.clock()
elapsed = now-ti
ti = now
print(func, elapsed)
import ssp
import numpy as np
import matplotlib.pyplot as plt
lap("Import")
# Load and do basic AR to reconstruct the spectrum
pcm = ssp.PulseCodeModulation()
wav = pcm.WavSource(file)
print("File:", file, "rate:", pcm.rate, "size:", wav.size)
if ssp.parameter("ZF", 0) == 1:
wav = ssp.ZeroFilter(wav)
f = ssp.Frame(wav, size=256, period=128)
f = ssp.Window(f, np.hanning(256))
print("frame:", f.shape[0], "x", f.shape[1])
lap("Frame")
e = ssp.Energy(f)
p = ssp.Periodogram(f)
lap("Periodogram")
order = pcm.speech_ar_order()
a = ssp.Autocorrelation(f)
a, g = ssp.ARLevinson(a, order)
lap("Levinson")
