diff options
Diffstat (limited to 'become_yukarin/voice_changer.py')
| -rw-r--r-- | become_yukarin/voice_changer.py | 31 |
1 files changed, 21 insertions, 10 deletions
diff --git a/become_yukarin/voice_changer.py b/become_yukarin/voice_changer.py index d1090a2..aeae0e6 100644 --- a/become_yukarin/voice_changer.py +++ b/become_yukarin/voice_changer.py @@ -39,12 +39,12 @@ class VoiceChanger(object): alpha=param.acoustic_feature_param.alpha, ) - _acoustic_feature_load_process = AcousticFeatureLoadProcess() + self._acoustic_feature_load_process = acoustic_feature_load_process = AcousticFeatureLoadProcess() - input_mean = _acoustic_feature_load_process(config.dataset.input_mean_path, test=True) - input_var = _acoustic_feature_load_process(config.dataset.input_var_path, test=True) - target_mean = _acoustic_feature_load_process(config.dataset.target_mean_path, test=True) - target_var = _acoustic_feature_load_process(config.dataset.target_var_path, test=True) + input_mean = acoustic_feature_load_process(config.dataset.input_mean_path, test=True) + input_var = acoustic_feature_load_process(config.dataset.input_var_path, test=True) + target_mean = acoustic_feature_load_process(config.dataset.target_mean_path, test=True) + target_var = acoustic_feature_load_process(config.dataset.target_var_path, test=True) self._feature_normalize = AcousticFeatureNormalizeProcess( mean=input_mean, var=input_var, @@ -61,12 +61,20 @@ class VoiceChanger(object): self._encode_feature = EncodeFeatureProcess(config.dataset.features) self._decode_feature = DecodeFeatureProcess(config.dataset.features, feature_sizes) - def __call__(self, voice_path: Path, out_sampling_rate: Optional[int] = None): - input = input_wave = self._wave_process(str(voice_path), test=True) + def convert_from_audio_path(self, input: Path, out_sampling_rate: Optional[int] = None): + input = self._wave_process(str(input), test=True) + input = self._feature_process(input, test=True) + return self.convert_from_feature(input, out_sampling_rate) + + def convert_from_feature_path(self, input: Path, out_sampling_rate: Optional[int] = None): + input = self._acoustic_feature_load_process(input, test=True) + return self.convert_from_feature(input, out_sampling_rate) + + def convert_from_feature(self, input: AcousticFeature, out_sampling_rate: Optional[int] = None): if out_sampling_rate is None: - out_sampling_rate = input_wave.sampling_rate + out_sampling_rate = self.config.dataset.param.voice_param.sample_rate - input = input_feature = self._feature_process(input, test=True) + input_feature = input input = self._feature_normalize(input, test=True) input = self._encode_feature(input, test=True) @@ -93,7 +101,7 @@ class VoiceChanger(object): voiced=out.voiced, ) - fftlen = pyworld.get_cheaptrick_fft_size(input_wave.sampling_rate) + fftlen = pyworld.get_cheaptrick_fft_size(out_sampling_rate) spectrogram = pysptk.mc2sp( out.mfcc, alpha=self._param.acoustic_feature_param.alpha, @@ -116,3 +124,6 @@ class VoiceChanger(object): ) return Wave(out, sampling_rate=out_sampling_rate) + + def __call__(self, voice_path: Path, out_sampling_rate: Optional[int] = None): + return self.convert_from_audio_path(voice_path, out_sampling_rate) |