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import pathlib |
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import numpy as np |
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import parselmouth |
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def norm_f0(f0): |
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f0 = np.log2(f0) |
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return f0 |
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def denorm_f0(f0, uv, pitch_padding=None): |
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f0 = 2 ** f0 |
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if uv is not None: |
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f0[uv > 0] = 0 |
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if pitch_padding is not None: |
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f0[pitch_padding] = 0 |
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return f0 |
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def interp_f0(f0, uv=None): |
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if uv is None: |
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uv = f0 == 0 |
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f0 = norm_f0(f0) |
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if sum(uv) == len(f0): |
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f0[uv] = -np.inf |
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elif sum(uv) > 0: |
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f0[uv] = np.interp(np.where(uv)[0], np.where(~uv)[0], f0[~uv]) |
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return denorm_f0(f0, uv=None), uv |
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def resample_align_curve(points: np.ndarray, original_timestep: float, target_timestep: float, align_length: int): |
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t_max = (len(points) - 1) * original_timestep |
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curve_interp = np.interp( |
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np.arange(0, t_max, target_timestep), |
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original_timestep * np.arange(len(points)), |
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points |
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).astype(points.dtype) |
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delta_l = align_length - len(curve_interp) |
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if delta_l < 0: |
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curve_interp = curve_interp[:align_length] |
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elif delta_l > 0: |
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curve_interp = np.concatenate((curve_interp, np.full(delta_l, fill_value=curve_interp[-1])), axis=0) |
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return curve_interp |
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def get_pitch_parselmouth(wav_data, hop_size, audio_sample_rate, interp_uv=True): |
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time_step = hop_size / audio_sample_rate |
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f0_min = 65. |
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f0_max = 1100. |
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f0 = ( |
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parselmouth.Sound(wav_data, sampling_frequency=audio_sample_rate) |
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.to_pitch_ac( |
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time_step=time_step, voicing_threshold=0.6, pitch_floor=f0_min, pitch_ceiling=f0_max |
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).selected_array["frequency"] |
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) |
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uv = f0 == 0 |
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if interp_uv: |
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f0, uv = interp_f0(f0, uv) |
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return time_step, f0, uv |
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rmvpe = None |
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def get_pitch_rmvpe(wav_data, hop_size, audio_sample_rate, interp_uv=True): |
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global rmvpe |
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if rmvpe is None: |
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from rmvpe import RMVPE |
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rmvpe = RMVPE(pathlib.Path(__file__).parent / 'assets' / 'rmvpe' / 'model.pt') |
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f0 = rmvpe.infer_from_audio(wav_data, sample_rate=audio_sample_rate) |
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uv = f0 == 0 |
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f0, uv = interp_f0(f0, uv) |
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time_step = hop_size / audio_sample_rate |
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length = (wav_data.shape[0] + hop_size - 1) // hop_size |
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f0_res = resample_align_curve(f0, 0.01, time_step, length) |
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uv_res = resample_align_curve(uv.astype(np.float32), 0.01, time_step, length) > 0.5 |
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if not interp_uv: |
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f0_res[uv_res] = 0 |
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return time_step, f0_res, uv_res |
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def get_pitch(algorithm, wav_data, hop_size, audio_sample_rate, interp_uv=True): |
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if algorithm == 'parselmouth': |
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return get_pitch_parselmouth(wav_data, hop_size, audio_sample_rate, interp_uv=interp_uv) |
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elif algorithm == 'rmvpe': |
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return get_pitch_rmvpe(wav_data, hop_size, audio_sample_rate, interp_uv=interp_uv) |
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else: |
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raise ValueError(f" [x] Unknown f0 extractor: {algorithm}") |
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