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import numpy as np |
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from modules.api.impl.handler.AudioHandler import AudioHandler |
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from modules.api.impl.model.audio_model import AdjustConfig |
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from modules.api.impl.model.chattts_model import ChatTTSConfig, InferConfig |
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from modules.api.impl.model.enhancer_model import EnhancerConfig |
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from modules.Enhancer.ResembleEnhance import apply_audio_enhance_full |
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from modules.normalization import text_normalize |
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from modules.speaker import Speaker |
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from modules.synthesize_audio import synthesize_audio |
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from modules.utils.audio import apply_prosody_to_audio_data |
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class TTSHandler(AudioHandler): |
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def __init__( |
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self, |
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text_content: str, |
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spk: Speaker, |
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tts_config: ChatTTSConfig, |
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infer_config: InferConfig, |
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adjust_config: AdjustConfig, |
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enhancer_config: EnhancerConfig, |
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): |
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assert isinstance(text_content, str), "text_content should be str" |
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assert isinstance(spk, Speaker), "spk should be Speaker" |
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assert isinstance( |
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tts_config, ChatTTSConfig |
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), "tts_config should be ChatTTSConfig" |
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assert isinstance( |
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infer_config, InferConfig |
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), "infer_config should be InferConfig" |
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assert isinstance( |
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adjust_config, AdjustConfig |
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), "adjest_config should be AdjustConfig" |
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assert isinstance( |
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enhancer_config, EnhancerConfig |
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), "enhancer_config should be EnhancerConfig" |
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self.text_content = text_content |
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self.spk = spk |
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self.tts_config = tts_config |
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self.infer_config = infer_config |
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self.adjest_config = adjust_config |
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self.enhancer_config = enhancer_config |
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self.validate() |
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def validate(self): |
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pass |
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def enqueue(self) -> tuple[np.ndarray, int]: |
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text = text_normalize(self.text_content) |
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tts_config = self.tts_config |
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infer_config = self.infer_config |
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adjust_config = self.adjest_config |
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enhancer_config = self.enhancer_config |
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sample_rate, audio_data = synthesize_audio( |
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text, |
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spk=self.spk, |
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temperature=tts_config.temperature, |
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top_P=tts_config.top_p, |
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top_K=tts_config.top_k, |
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prompt1=tts_config.prompt1, |
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prompt2=tts_config.prompt2, |
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prefix=tts_config.prefix, |
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infer_seed=infer_config.seed, |
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batch_size=infer_config.batch_size, |
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spliter_threshold=infer_config.spliter_threshold, |
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end_of_sentence=infer_config.eos, |
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) |
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if enhancer_config.enabled: |
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nfe = enhancer_config.nfe |
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solver = enhancer_config.solver |
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lambd = enhancer_config.lambd |
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tau = enhancer_config.tau |
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audio_data, sample_rate = apply_audio_enhance_full( |
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audio_data=audio_data, |
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sr=sample_rate, |
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nfe=nfe, |
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solver=solver, |
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lambd=lambd, |
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tau=tau, |
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) |
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audio_data = apply_prosody_to_audio_data( |
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audio_data=audio_data, |
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rate=adjust_config.speed_rate, |
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pitch=adjust_config.pitch, |
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volume=adjust_config.volume_gain_db, |
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sr=sample_rate, |
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) |
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return audio_data, sample_rate |
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