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# -*- coding: utf-8 -*-
import numpy as np
from scipy.signal import correlate2d
from skimage.util import view_as_windows
class WSOLA(object):
def __init__(self, fs, speech_rate, shiftms=10):
self.fs = fs
self.speech_rate = speech_rate
self.shiftms = shiftms # Hs的时间
self.sl = int(self.fs * self.shiftms / 1000) # Hs的长度
self.fl = self.sl * 2 # 帧长 Hs长度的两倍
self.epstep = int(self.sl * self.speech_rate) # Ha的长度
self.win = np.hanning(self.fl) # 窗函数
def duration_modification(self, x):
wlen = len(x) # Lin
#Lout = Lin/rate
wsolaed = np.zeros(int(wlen / self.speech_rate), dtype='d')
# 初始化
sp = self.sl * 2 # x'm的中心
rp = sp + self.sl # x~m的中心
ep = sp + self.epstep # x+(m+1)的中心
outp = self.sl
# allocate first frame of waveform to outp
wsolaed[:outp] = x[:outp]
while wlen > ep + self.fl:
# copy wavform
ref = x[rp - self.sl:rp + self.sl] # x~m
buff = x[ep - self.fl:ep + self.fl] # 搜索区域
# search minimum distance bepween ref and buff
delta = self._search_minimum_distance(ref, buff)
epd = ep + delta
# store WSOLAed waveform using over-lap add
spdata = x[sp:sp + self.sl] * self.win[self.sl:] # x'm的右半帧
epdata = x[epd - self.sl:epd] * self.win[:self.sl] # x~m的左半帧
if len(spdata) == len(wsolaed[outp:outp + self.sl]):
wsolaed[outp:outp + self.sl] = spdata + epdata
else:
wsolaed_len = len(wsolaed[outp:outp + self.sl])
wsolaed[outp:outp + self.sl] = spdata[:wsolaed_len] + \
epdata[:wsolaed_len]
outp += self.sl
# 计算下一帧的起始位置
sp = epd
rp = sp + self.sl
ep += self.epstep
return wsolaed
def _search_minimum_distance(self, ref, buff):
if len(ref) < self.fl:
ref = np.r_[ref, np.zeros(self.fl - len(ref))]
# slicing and windowing one sample by one
buffmat = view_as_windows(buff, self.fl) * self.win
refwin = np.array(ref * self.win).reshape(1, self.fl)
corr = correlate2d(buffmat, refwin, mode='valid')
return np.argmax(corr) - self.sl |