mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-05-06 11:39:01 +08:00
New feature of real-time voice changing: formant shift adjustment (#1999)
* add formant shift for realtime-gui * chore(i18n): sync locale on dev * chore(format): run black on dev * fix --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
This commit is contained in:
yxlllc
GitHub
parent
189eef5936
commit
0ab3a3296e
@ -1 +1 @@
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{"pth_path": "assets/weights/kikiV1.pth", "index_path": "logs/kikiV1.index", "sg_hostapi": "MME", "sg_wasapi_exclusive": false, "sg_input_device": "VoiceMeeter Output (VB-Audio Vo", "sg_output_device": "VoiceMeeter Input (VB-Audio Voi", "sr_type": "sr_device", "threhold": -60.0, "pitch": 12.0, "rms_mix_rate": 0.5, "index_rate": 0.0, "block_time": 0.15, "crossfade_length": 0.08, "extra_time": 2.0, "n_cpu": 4.0, "use_jit": false, "use_pv": false, "f0method": "fcpe"}
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{"pth_path": "assets/weights/kikiV1.pth", "index_path": "logs/kikiV1.index", "sg_hostapi": "MME", "sg_wasapi_exclusive": false, "sg_input_device": "VoiceMeeter Output (VB-Audio Vo", "sg_output_device": "VoiceMeeter Input (VB-Audio Voi", "sr_type": "sr_device", "threhold": -60.0, "pitch": 12.0, "formant": 0.0, "rms_mix_rate": 0.5, "index_rate": 0.0, "block_time": 0.15, "crossfade_length": 0.08, "extra_time": 2.0, "n_cpu": 4.0, "use_jit": false, "use_pv": false, "f0method": "fcpe"}
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20
gui_v1.py
20
gui_v1.py
@ -114,6 +114,7 @@ if __name__ == "__main__":
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self.pth_path: str = ""
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self.index_path: str = ""
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self.pitch: int = 0
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self.formant: float = 0.0
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self.sr_type: str = "sr_model"
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self.block_time: float = 0.25 # s
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self.threhold: int = -60
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@ -212,6 +213,7 @@ if __name__ == "__main__":
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"sr_type": "sr_model",
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"threhold": -60,
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"pitch": 0,
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"formant": 0.0,
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"index_rate": 0,
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"rms_mix_rate": 0,
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"block_time": 0.25,
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@ -354,6 +356,17 @@ if __name__ == "__main__":
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enable_events=True,
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),
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],
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[
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sg.Text(i18n("共振偏移")),
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sg.Slider(
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range=(-5, 5),
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key="formant",
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resolution=0.01,
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orientation="h",
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default_value=data.get("formant", 0.0),
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enable_events=True,
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),
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],
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[
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sg.Text(i18n("Index Rate")),
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sg.Slider(
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@ -579,6 +592,7 @@ if __name__ == "__main__":
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],
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"threhold": values["threhold"],
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"pitch": values["pitch"],
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"formant": values["formant"],
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"rms_mix_rate": values["rms_mix_rate"],
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"index_rate": values["index_rate"],
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# "device_latency": values["device_latency"],
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@ -621,6 +635,10 @@ if __name__ == "__main__":
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self.gui_config.pitch = values["pitch"]
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if hasattr(self, "rvc"):
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self.rvc.change_key(values["pitch"])
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elif event == "formant":
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self.gui_config.formant = values["formant"]
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if hasattr(self, "rvc"):
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self.rvc.change_formant(values["formant"])
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elif event == "index_rate":
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self.gui_config.index_rate = values["index_rate"]
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if hasattr(self, "rvc"):
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@ -679,6 +697,7 @@ if __name__ == "__main__":
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]
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self.gui_config.threhold = values["threhold"]
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self.gui_config.pitch = values["pitch"]
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self.gui_config.formant = values["formant"]
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self.gui_config.block_time = values["block_time"]
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self.gui_config.crossfade_time = values["crossfade_length"]
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self.gui_config.extra_time = values["extra_time"]
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@ -703,6 +722,7 @@ if __name__ == "__main__":
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torch.cuda.empty_cache()
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self.rvc = rtrvc.RVC(
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self.gui_config.pitch,
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self.gui_config.formant,
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self.gui_config.pth_path,
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self.gui_config.index_path,
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self.gui_config.index_rate,
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modify model information (only supported for small model files extracted from the 'weights' folder)",
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"停止音频转换": "Stop audio conversion",
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"全流程结束！": "All processes have been completed!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Refresh voice list and index path",
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"加载模型": "Load model",
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"加载预训练底模D路径": "Load pre-trained base model D path:",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modificar la información del modelo (solo admite archivos de modelos pequeños extraídos en la carpeta weights)",
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"停止音频转换": "Detener la conversión de audio",
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"全流程结束！": "¡Todo el proceso ha terminado!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Actualizar la lista de modelos e índice de rutas",
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"加载模型": "Cargar modelo",
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"加载预训练底模D路径": "Cargue la ruta del modelo D base pre-entrenada.",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modifier les informations du modèle (uniquement pris en charge pour les petits fichiers de modèle extraits du dossier 'weights')",
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"停止音频转换": "Arrêter la conversion audio",
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"全流程结束！": "Toutes les étapes ont été terminées !",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Actualiser la liste des voix et le vers l'index.",
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"加载模型": "Charger le modèle.",
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"加载预训练底模D路径": "Charger le chemin du modèle de base pré-entraîné D :",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modifica le informazioni sul modello (supportato solo per i file di modello di piccole dimensioni estratti dalla cartella 'weights')",
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"停止音频转换": "Arresta la conversione audio",
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"全流程结束！": "Tutti i processi sono stati completati!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Aggiorna l'elenco delle voci e il percorso dell'indice",
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"加载模型": "Carica modello",
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"加载预训练底模D路径": "Carica il percorso D del modello base pre-addestrato:",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "モデル情報の修正(weightsフォルダから抽出された小さなモデルファイルのみ対応)",
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"停止音频转换": "音声変換を停止",
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"全流程结束！": "全工程が完了！",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "音源リストとインデックスパスの更新",
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"加载模型": "モデルをロード",
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"加载预训练底模D路径": "事前学習済みのDモデルのパス",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "모델 정보 수정(오직 weights 폴더 아래에서 추출된 작은 모델 파일만 지원)",
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"停止音频转换": "오디오 변환 중지",
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"全流程结束！": "전체 과정 완료!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "음색 목록 및 인덱스 경로 새로고침",
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"加载模型": "모델 로드",
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"加载预训练底模D路径": "미리 훈련된 베이스 모델 D 경로 로드",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modificar informações do modelo (suportado apenas para arquivos de modelo pequenos extraídos da pasta 'weights')",
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"停止音频转换": "Conversão de áudio",
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"全流程结束！": "Todos os processos foram concluídos!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Atualizar lista de voz e caminho do Index",
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"加载模型": "Modelo",
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"加载预训练底模D路径": "Carregue o caminho D do modelo base pré-treinado:",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Изменить информацию о модели (работает только с маленькими моделями, взятыми из папки 'weights')",
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"停止音频转换": "Закончить конвертацию аудио",
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"全流程结束！": "Все процессы завершены!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Обновить список голосов и индексов",
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"加载模型": "Загрузить модель",
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"加载预训练底模D路径": "Путь к предварительно обученной базовой модели D:",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Model bilgilerini düzenle (sadece 'weights' klasöründen çıkarılan küçük model dosyaları desteklenir)",
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"停止音频转换": "Ses dönüştürmeyi durdur",
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"全流程结束！": "Tüm işlemler tamamlandı!",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "Ses listesini ve indeks yolunu yenile",
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"加载模型": "Model yükle",
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"加载预训练底模D路径": "Önceden eğitilmiş temel D modelini yükleme yolu:",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "修改模型信息(仅支持weights文件夹下提取的小模型文件)",
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"停止音频转换": "停止音频转换",
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"全流程结束！": "全流程结束！",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "刷新音色列表和索引路径",
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"加载模型": "加载模型",
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"加载预训练底模D路径": "加载预训练底模D路径",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "修改模型資訊(僅支援weights資料夾下提取的小模型檔案)",
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"停止音频转换": "停止音訊轉換",
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"全流程结束！": "全流程结束！",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "刷新音色列表和索引路徑",
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"加载模型": "載入模型",
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"加载预训练底模D路径": "加載預訓練底模D路徑",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "修改模型資訊(僅支援weights資料夾下提取的小模型檔案)",
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"停止音频转换": "停止音訊轉換",
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"全流程结束！": "全流程结束！",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "刷新音色列表和索引路徑",
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"加载模型": "載入模型",
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"加载预训练底模D路径": "加載預訓練底模D路徑",
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@ -37,6 +37,7 @@
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"修改模型信息(仅支持weights文件夹下提取的小模型文件)": "修改模型資訊(僅支援weights資料夾下提取的小模型檔案)",
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"停止音频转换": "停止音訊轉換",
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"全流程结束！": "全流程结束！",
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"共振偏移": "共振偏移",
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"刷新音色列表和索引路径": "刷新音色列表和索引路徑",
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"加载模型": "載入模型",
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"加载预训练底模D路径": "加載預訓練底模D路徑",
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@ -10,7 +10,6 @@ from torch import nn
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from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
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from torch.nn import functional as F
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from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
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from infer.lib.infer_pack import attentions, commons, modules
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from infer.lib.infer_pack.commons import get_padding, init_weights
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@ -250,7 +249,17 @@ class Generator(torch.nn.Module):
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if gin_channels != 0:
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self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
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def forward(self, x: torch.Tensor, g: Optional[torch.Tensor] = None):
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def forward(
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self,
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x: torch.Tensor,
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g: Optional[torch.Tensor] = None,
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n_res: Optional[torch.Tensor] = None,
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):
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if n_res is not None:
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assert isinstance(n_res, torch.Tensor)
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n = int(n_res.item())
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if n != x.shape[-1]:
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x = F.interpolate(x, size=n, mode="linear")
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x = self.conv_pre(x)
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if g is not None:
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x = x + self.cond(g)
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@ -529,9 +538,22 @@ class GeneratorNSF(torch.nn.Module):
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self.lrelu_slope = modules.LRELU_SLOPE
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def forward(self, x, f0, g: Optional[torch.Tensor] = None):
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def forward(
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self,
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x,
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f0,
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g: Optional[torch.Tensor] = None,
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n_res: Optional[torch.Tensor] = None,
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):
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har_source, noi_source, uv = self.m_source(f0, self.upp)
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har_source = har_source.transpose(1, 2)
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if n_res is not None:
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assert isinstance(n_res, torch.Tensor)
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n = int(n_res.item())
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if n * self.upp != har_source.shape[-1]:
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har_source = F.interpolate(har_source, size=n * self.upp, mode="linear")
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if n != x.shape[-1]:
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x = F.interpolate(x, size=n, mode="linear")
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x = self.conv_pre(x)
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if g is not None:
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x = x + self.cond(g)
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@ -558,6 +580,7 @@ class GeneratorNSF(torch.nn.Module):
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x = F.leaky_relu(x)
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x = self.conv_post(x)
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x = torch.tanh(x)
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return x
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def remove_weight_norm(self):
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@ -748,6 +771,7 @@ class SynthesizerTrnMs256NSFsid(nn.Module):
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sid: torch.Tensor,
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skip_head: Optional[torch.Tensor] = None,
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return_length: Optional[torch.Tensor] = None,
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return_length2: Optional[torch.Tensor] = None,
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):
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g = self.emb_g(sid).unsqueeze(-1)
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if skip_head is not None and return_length is not None:
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@ -767,7 +791,7 @@ class SynthesizerTrnMs256NSFsid(nn.Module):
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m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
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z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
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z = self.flow(z_p, x_mask, g=g, reverse=True)
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o = self.dec(z * x_mask, nsff0, g=g)
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o = self.dec(z * x_mask, nsff0, g=g, n_res=return_length2)
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return o, x_mask, (z, z_p, m_p, logs_p)
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@ -963,6 +987,7 @@ class SynthesizerTrnMs256NSFsid_nono(nn.Module):
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sid: torch.Tensor,
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skip_head: Optional[torch.Tensor] = None,
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return_length: Optional[torch.Tensor] = None,
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return_length2: Optional[torch.Tensor] = None,
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):
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g = self.emb_g(sid).unsqueeze(-1)
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if skip_head is not None and return_length is not None:
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@ -981,7 +1006,7 @@ class SynthesizerTrnMs256NSFsid_nono(nn.Module):
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m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
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z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
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z = self.flow(z_p, x_mask, g=g, reverse=True)
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o = self.dec(z * x_mask, g=g)
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o = self.dec(z * x_mask, g=g, n_res=return_length2)
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return o, x_mask, (z, z_p, m_p, logs_p)
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@ -15,6 +15,7 @@ import torch
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import torch.nn as nn
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import torch.nn.functional as F
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import torchcrepe
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from torchaudio.transforms import Resample
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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@ -40,6 +41,7 @@ class RVC:
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def __init__(
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self,
|
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key,
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formant,
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pth_path,
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index_path,
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index_rate,
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@ -68,6 +70,7 @@ class RVC:
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# device="cpu"########强制cpu测试
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self.device = config.device
|
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self.f0_up_key = key
|
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self.formant_shift = formant
|
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self.f0_min = 50
|
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self.f0_max = 1100
|
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self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
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@ -90,6 +93,8 @@ class RVC:
|
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1024, device=self.device, dtype=torch.float32
|
||||
)
|
||||
|
||||
self.resample_kernel = {}
|
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|
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if last_rvc is None:
|
||||
models, _, _ = fairseq.checkpoint_utils.load_model_ensemble_and_task(
|
||||
["assets/hubert/hubert_base.pt"],
|
||||
@ -187,6 +192,9 @@ class RVC:
|
||||
def change_key(self, new_key):
|
||||
self.f0_up_key = new_key
|
||||
|
||||
def change_formant(self, new_formant):
|
||||
self.formant_shift = new_formant
|
||||
|
||||
def change_index_rate(self, new_index_rate):
|
||||
if new_index_rate != 0 and self.index_rate == 0:
|
||||
self.index = faiss.read_index(self.index_path)
|
||||
@ -390,12 +398,14 @@ class RVC:
|
||||
printt("Index search FAILED")
|
||||
t3 = ttime()
|
||||
p_len = input_wav.shape[0] // 160
|
||||
factor = pow(2, self.formant_shift / 12)
|
||||
return_length2 = int(np.ceil(return_length * factor))
|
||||
if self.if_f0 == 1:
|
||||
f0_extractor_frame = block_frame_16k + 800
|
||||
if f0method == "rmvpe":
|
||||
f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1) - 160
|
||||
pitch, pitchf = self.get_f0(
|
||||
input_wav[-f0_extractor_frame:], self.f0_up_key, self.n_cpu, f0method
|
||||
input_wav[-f0_extractor_frame:], self.f0_up_key - self.formant_shift, self.n_cpu, f0method
|
||||
)
|
||||
shift = block_frame_16k // 160
|
||||
self.cache_pitch[:-shift] = self.cache_pitch[shift:].clone()
|
||||
@ -403,13 +413,14 @@ class RVC:
|
||||
self.cache_pitch[4 - pitch.shape[0] :] = pitch[3:-1]
|
||||
self.cache_pitchf[4 - pitch.shape[0] :] = pitchf[3:-1]
|
||||
cache_pitch = self.cache_pitch[None, -p_len:]
|
||||
cache_pitchf = self.cache_pitchf[None, -p_len:]
|
||||
cache_pitchf = self.cache_pitchf[None, -p_len:] * return_length2 / return_length
|
||||
t4 = ttime()
|
||||
feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
|
||||
feats = feats[:, :p_len, :]
|
||||
p_len = torch.LongTensor([p_len]).to(self.device)
|
||||
sid = torch.LongTensor([0]).to(self.device)
|
||||
skip_head = torch.LongTensor([skip_head])
|
||||
return_length2 = torch.LongTensor([return_length2])
|
||||
return_length = torch.LongTensor([return_length])
|
||||
with torch.no_grad():
|
||||
if self.if_f0 == 1:
|
||||
@ -421,10 +432,23 @@ class RVC:
|
||||
sid,
|
||||
skip_head,
|
||||
return_length,
|
||||
return_length2,
|
||||
)
|
||||
else:
|
||||
infered_audio, _, _ = self.net_g.infer(
|
||||
feats, p_len, sid, skip_head, return_length
|
||||
feats, p_len, sid, skip_head, return_length, return_length2
|
||||
)
|
||||
infered_audio = infered_audio.squeeze(1).float()
|
||||
upp_res = int(np.floor(factor * self.tgt_sr // 100))
|
||||
if upp_res != self.tgt_sr // 100:
|
||||
if upp_res not in self.resample_kernel:
|
||||
self.resample_kernel[upp_res] = Resample(
|
||||
orig_freq=upp_res,
|
||||
new_freq=self.tgt_sr // 100,
|
||||
dtype=torch.float32,
|
||||
).to(self.device)
|
||||
infered_audio = self.resample_kernel[upp_res](
|
||||
infered_audio[:, : return_length * upp_res]
|
||||
)
|
||||
t5 = ttime()
|
||||
printt(
|
||||
@ -434,4 +458,4 @@ class RVC:
|
||||
t4 - t3,
|
||||
t5 - t4,
|
||||
)
|
||||
return infered_audio.squeeze().float()
|
||||
return infered_audio.squeeze()
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user