Python pyworld.d4c方法代碼示例

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def world_decompose(wav, fs, frame_period = 5.0):

    # Decompose speech signal into f0, spectral envelope and aperiodicity using WORLD
    wav = wav.astype(np.float64)
    f0, timeaxis = pyworld.harvest(wav, fs, frame_period = frame_period, f0_floor = 71.0, f0_ceil = 800.0)
    sp = pyworld.cheaptrick(wav, f0, timeaxis, fs)
    ap = pyworld.d4c(wav, f0, timeaxis, fs)

    return f0, timeaxis, sp, ap 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def analyze(self, x):
        """Analyze acoustic features based on WORLD

        analyze F0, spectral envelope, aperiodicity

        Paramters
        ---------
        x : array, shape (`T`)
            monoral speech signal in time domain

        Returns
        ---------
        f0 : array, shape (`T`,)
            F0 sequence
        spc : array, shape (`T`, `fftl / 2 + 1`)
            Spectral envelope sequence
        ap: array, shape (`T`, `fftl / 2 + 1`)
            aperiodicity sequence

        """
        f0, time_axis = pyworld.harvest(x, self.fs, f0_floor=self.minf0,
                                        f0_ceil=self.maxf0, frame_period=self.shiftms)
        spc = pyworld.cheaptrick(x, f0, time_axis, self.fs,
                                 fft_size=self.fftl)
        ap = pyworld.d4c(x, f0, time_axis, self.fs, fft_size=self.fftl)

        assert spc.shape == ap.shape
        return f0, spc, ap 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def cal_mcep(wav_ori, fs=SAMPLE_RATE, ispad=False, frame_period=0.005, dim=FEATURE_DIM, fft_size=FFTSIZE):
    '''cal mcep given wav singnal
        the frame_period used only for pad_wav_to_get_fixed_frames
    '''
    if ispad:
        wav, pad_length = pad_wav_to_get_fixed_frames(
            wav_ori, frames=FRAMES, frame_period=frame_period, sr=fs)
    else:
        wav = wav_ori
    # Harvest F0 extraction algorithm.
    f0, timeaxis = pyworld.harvest(wav, fs)

    # CheapTrick harmonic spectral envelope estimation algorithm.
    sp = pyworld.cheaptrick(wav, f0, timeaxis, fs, fft_size=fft_size)

    # D4C aperiodicity estimation algorithm.
    ap = pyworld.d4c(wav, f0, timeaxis, fs, fft_size=fft_size)
    # feature reduction nxdim
    coded_sp = pyworld.code_spectral_envelope(sp, fs, dim)
    # log
    coded_sp = coded_sp.T  # dim x n

    res = {
        'f0': f0,  # n
        'ap': ap,  # n*fftsize//2+1
        'sp': sp,  # n*fftsize//2+1
        'coded_sp': coded_sp,  # dim * n
    }
    return res 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def __call__(self, data: Wave, test=None):
        x = data.wave.astype(numpy.float64)
        fs = data.sampling_rate

        if self._f0_estimating_method == 'dio':
            _f0, t = pyworld.dio(
                x,
                fs,
                frame_period=self._frame_period,
                f0_floor=self._f0_floor,
                f0_ceil=self._f0_ceil,
            )
        else:
            from world4py.np import apis
            _f0, t = apis.harvest(
                x,
                fs,
                frame_period=self._frame_period,
                f0_floor=self._f0_floor,
                f0_ceil=self._f0_ceil,
            )
        f0 = pyworld.stonemask(x, _f0, t, fs)
        spectrogram = pyworld.cheaptrick(x, f0, t, fs)
        aperiodicity = pyworld.d4c(x, f0, t, fs)

        mfcc = pysptk.sp2mc(spectrogram, order=self._order, alpha=self._alpha)
        voiced = ~(f0 == 0)  # type: numpy.ndarray

        feature = AcousticFeature(
            f0=f0[:, None].astype(self._dtype),
            spectrogram=spectrogram.astype(self._dtype),
            aperiodicity=aperiodicity.astype(self._dtype),
            mfcc=mfcc.astype(self._dtype),
            voiced=voiced[:, None],
        )
        feature.validate()
        return feature 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def world_decompose(wav, fs, frame_period=5.0):
    # Decompose speech signal into f0, spectral envelope and aperiodicity using WORLD
    wav = wav.astype(np.float64)
    f0, timeaxis = pyworld.harvest(wav, fs, frame_period=frame_period, f0_floor=71.0, f0_ceil=800.0)
    sp = pyworld.cheaptrick(wav, f0, timeaxis, fs)
    ap = pyworld.d4c(wav, f0, timeaxis, fs)

    return f0, timeaxis, sp, ap 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def extract(cls, wave: Wave, frame_period, f0_floor, f0_ceil, fft_length, order, alpha, dtype):
        x = wave.wave.astype(numpy.float64)
        fs = wave.sampling_rate

        f0, t = cls.extract_f0(x=x, fs=fs, frame_period=frame_period, f0_floor=f0_floor, f0_ceil=f0_ceil)
        sp = pyworld.cheaptrick(x, f0, t, fs, fft_size=fft_length)
        ap = pyworld.d4c(x, f0, t, fs, fft_size=fft_length)

        mc = pysptk.sp2mc(sp, order=order, alpha=alpha)
        coded_ap = pyworld.code_aperiodicity(ap, fs)
        voiced: numpy.ndarray = ~(f0 == 0)

        if len(x) % fft_length > 0:
            f0 = f0[:-1]
            t = t[:-1]
            sp = sp[:-1]
            ap = ap[:-1]
            mc = mc[:-1]
            coded_ap = coded_ap[:-1]
            voiced = voiced[:-1]

        feature = AcousticFeature(
            f0=f0[:, None],
            sp=sp,
            ap=ap,
            coded_ap=coded_ap,
            mc=mc,
            voiced=voiced[:, None],
        )
        feature = feature.astype_only_float(dtype)
        return feature 

# 需要導入模塊: import pyworld [as 別名]
# 或者: from pyworld import d4c [as 別名]
def main(args):
    if os.path.isdir('test'):
        rmtree('test')
    os.mkdir('test')

    x, fs = sf.read('utterance/vaiueo2d.wav')
    # x, fs = librosa.load('utterance/vaiueo2d.wav', dtype=np.float64)

    # 1. A convient way
    f0, sp, ap = pw.wav2world(x, fs)    # use default options
    y = pw.synthesize(f0, sp, ap, fs, pw.default_frame_period)

    # 2. Step by step
    # 2-1 Without F0 refinement
    _f0, t = pw.dio(x, fs, f0_floor=50.0, f0_ceil=600.0,
                    channels_in_octave=2,
                    frame_period=args.frame_period,
                    speed=args.speed)
    _sp = pw.cheaptrick(x, _f0, t, fs)
    _ap = pw.d4c(x, _f0, t, fs)
    _y = pw.synthesize(_f0, _sp, _ap, fs, args.frame_period)
    # librosa.output.write_wav('test/y_without_f0_refinement.wav', _y, fs)
    sf.write('test/y_without_f0_refinement.wav', _y, fs)

    # 2-2 DIO with F0 refinement (using Stonemask)
    f0 = pw.stonemask(x, _f0, t, fs)
    sp = pw.cheaptrick(x, f0, t, fs)
    ap = pw.d4c(x, f0, t, fs)
    y = pw.synthesize(f0, sp, ap, fs, args.frame_period)
    # librosa.output.write_wav('test/y_with_f0_refinement.wav', y, fs)
    sf.write('test/y_with_f0_refinement.wav', y, fs)

    # 2-3 Harvest with F0 refinement (using Stonemask)
    _f0_h, t_h = pw.harvest(x, fs)
    f0_h = pw.stonemask(x, _f0_h, t_h, fs)
    sp_h = pw.cheaptrick(x, f0_h, t_h, fs)
    ap_h = pw.d4c(x, f0_h, t_h, fs)
    y_h = pw.synthesize(f0_h, sp_h, ap_h, fs, pw.default_frame_period)
    # librosa.output.write_wav('test/y_harvest_with_f0_refinement.wav', y_h, fs)
    sf.write('test/y_harvest_with_f0_refinement.wav', y_h, fs)

    # Comparison
    savefig('test/wavform.png', [x, _y, y])
    savefig('test/sp.png', [_sp, sp])
    savefig('test/ap.png', [_ap, ap], log=False)
    savefig('test/f0.png', [_f0, f0])

    print('Please check "test" directory for output files')