Spaces:
Running
Running
| import os | |
| import torch | |
| from InferenceInterfaces.Controllability.GAN import GanWrapper | |
| from InferenceInterfaces.ToucanTTSInterface import ToucanTTSInterface | |
| from Utility.storage_config import MODELS_DIR | |
| class ControllableInterface: | |
| def __init__(self, gpu_id="cpu", available_artificial_voices=1000): | |
| if gpu_id == "cpu": | |
| os.environ["CUDA_VISIBLE_DEVICES"] = "" | |
| else: | |
| os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" | |
| os.environ["CUDA_VISIBLE_DEVICES"] = f"{gpu_id}" | |
| self.device = "cuda" if torch.cuda.is_available() else "cpu" | |
| self.model = ToucanTTSInterface(device=self.device, tts_model_path="Meta") | |
| self.wgan = GanWrapper(os.path.join(MODELS_DIR, "Embedding", "embedding_gan.pt"), device=self.device) | |
| self.generated_speaker_embeds = list() | |
| self.available_artificial_voices = available_artificial_voices | |
| self.current_language = "English" | |
| self.current_accent = "English" | |
| self.language_id_lookup = { | |
| "English" : "en", | |
| "German" : "de", | |
| "Greek" : "el", | |
| "Spanish" : "es", | |
| "Finnish" : "fi", | |
| "Russian" : "ru", | |
| "Hungarian" : "hu", | |
| "Dutch" : "nl", | |
| "French" : "fr", | |
| 'Polish' : "pl", | |
| 'Portuguese': "pt", | |
| 'Italian' : "it", | |
| 'Chinese' : "cmn", | |
| 'Vietnamese': "vi", | |
| } | |
| def read(self, | |
| prompt, | |
| language, | |
| accent, | |
| voice_seed, | |
| duration_scaling_factor, | |
| pause_duration_scaling_factor, | |
| pitch_variance_scale, | |
| energy_variance_scale, | |
| emb_slider_1, | |
| emb_slider_2, | |
| emb_slider_3, | |
| emb_slider_4, | |
| emb_slider_5, | |
| emb_slider_6 | |
| ): | |
| language = language.split()[0] | |
| accent = accent.split()[0] | |
| if self.current_language != language: | |
| self.model.set_phonemizer_language(self.language_id_lookup[language]) | |
| self.current_language = language | |
| if self.current_accent != accent: | |
| self.model.set_accent_language(self.language_id_lookup[accent]) | |
| self.current_accent = accent | |
| self.wgan.set_latent(voice_seed) | |
| controllability_vector = torch.tensor([emb_slider_1, | |
| emb_slider_2, | |
| emb_slider_3, | |
| emb_slider_4, | |
| emb_slider_5, | |
| emb_slider_6], dtype=torch.float32) | |
| embedding = self.wgan.modify_embed(controllability_vector) | |
| self.model.set_utterance_embedding(embedding=embedding) | |
| phones = self.model.text2phone.get_phone_string(prompt) | |
| if len(phones) > 1800: | |
| if language == "German": | |
| prompt = "Deine Eingabe war zu lang. Bitte versuche es entweder mit einem kürzeren Text oder teile ihn in mehrere Teile auf." | |
| elif language == "Greek": | |
| prompt = "Η εισήγησή σας ήταν πολύ μεγάλη. Παρακαλώ δοκιμάστε είτε ένα μικρότερο κείμενο είτε χωρίστε το σε διάφορα μέρη." | |
| elif language == "Spanish": | |
| prompt = "Su entrada es demasiado larga. Por favor, intente un texto más corto o divídalo en varias partes." | |
| elif language == "Finnish": | |
| prompt = "Vastauksesi oli liian pitkä. Kokeile joko lyhyempää tekstiä tai jaa se useampaan osaan." | |
| elif language == "Russian": | |
| prompt = "Ваш текст слишком длинный. Пожалуйста, попробуйте либо сократить текст, либо разделить его на несколько частей." | |
| elif language == "Hungarian": | |
| prompt = "Túl hosszú volt a bevitele. Kérjük, próbáljon meg rövidebb szöveget írni, vagy ossza több részre." | |
| elif language == "Dutch": | |
| prompt = "Uw input was te lang. Probeer een kortere tekst of splits het in verschillende delen." | |
| elif language == "French": | |
| prompt = "Votre saisie était trop longue. Veuillez essayer un texte plus court ou le diviser en plusieurs parties." | |
| elif language == 'Polish': | |
| prompt = "Twój wpis był zbyt długi. Spróbuj skrócić tekst lub podzielić go na kilka części." | |
| elif language == 'Portuguese': | |
| prompt = "O seu contributo foi demasiado longo. Por favor, tente um texto mais curto ou divida-o em várias partes." | |
| elif language == 'Italian': | |
| prompt = "Il tuo input era troppo lungo. Per favore, prova un testo più corto o dividilo in più parti." | |
| elif language == 'Chinese': | |
| prompt = "你的输入太长了。请尝试使用较短的文本或将其拆分为多个部分。" | |
| elif language == 'Vietnamese': | |
| prompt = "Đầu vào của bạn quá dài. Vui lòng thử một văn bản ngắn hơn hoặc chia nó thành nhiều phần." | |
| else: | |
| prompt = "Your input was too long. Please try either a shorter text or split it into several parts." | |
| if self.current_language != "English": | |
| self.model.set_phonemizer_language(self.language_id_lookup["English"]) | |
| self.current_language = "English" | |
| if self.current_accent != "English": | |
| self.model.set_accent_language(self.language_id_lookup["English"]) | |
| self.current_accent = "English" | |
| print(prompt) | |
| wav, fig = self.model(prompt, | |
| input_is_phones=False, | |
| duration_scaling_factor=duration_scaling_factor, | |
| pitch_variance_scale=pitch_variance_scale, | |
| energy_variance_scale=energy_variance_scale, | |
| pause_duration_scaling_factor=pause_duration_scaling_factor, | |
| return_plot_as_filepath=True) | |
| wav = wav.cpu().numpy() | |
| wav = [val for val in wav for _ in (0, 1)] # doubling the sampling rate for better compatibility (24kHz is not as standard as 48kHz) | |
| return 48000, wav, fig | |