from pathlib import Path import gradio as gr import torch torch._C._jit_set_profiling_mode(False) params = { 'activate': True, 'speaker': 'en_56', 'language': 'en', 'model_id': 'v3_en', 'sample_rate': 48000, 'device': 'cpu', } current_params = params.copy() voices_by_gender = ['en_99', 'en_45', 'en_18', 'en_117', 'en_49', 'en_51', 'en_68', 'en_0', 'en_26', 'en_56', 'en_74', 'en_5', 'en_38', 'en_53', 'en_21', 'en_37', 'en_107', 'en_10', 'en_82', 'en_16', 'en_41', 'en_12', 'en_67', 'en_61', 'en_14', 'en_11', 'en_39', 'en_52', 'en_24', 'en_97', 'en_28', 'en_72', 'en_94', 'en_36', 'en_4', 'en_43', 'en_88', 'en_25', 'en_65', 'en_6', 'en_44', 'en_75', 'en_91', 'en_60', 'en_109', 'en_85', 'en_101', 'en_108', 'en_50', 'en_96', 'en_64', 'en_92', 'en_76', 'en_33', 'en_116', 'en_48', 'en_98', 'en_86', 'en_62', 'en_54', 'en_95', 'en_55', 'en_111', 'en_3', 'en_83', 'en_8', 'en_47', 'en_59', 'en_1', 'en_2', 'en_7', 'en_9', 'en_13', 'en_15', 'en_17', 'en_19', 'en_20', 'en_22', 'en_23', 'en_27', 'en_29', 'en_30', 'en_31', 'en_32', 'en_34', 'en_35', 'en_40', 'en_42', 'en_46', 'en_57', 'en_58', 'en_63', 'en_66', 'en_69', 'en_70', 'en_71', 'en_73', 'en_77', 'en_78', 'en_79', 'en_80', 'en_81', 'en_84', 'en_87', 'en_89', 'en_90', 'en_93', 'en_100', 'en_102', 'en_103', 'en_104', 'en_105', 'en_106', 'en_110', 'en_112', 'en_113', 'en_114', 'en_115'] wav_idx = 0 def load_model(): model, example_text = torch.hub.load(repo_or_dir='snakers4/silero-models', model='silero_tts', language=params['language'], speaker=params['model_id']) model.to(params['device']) return model model = load_model() def remove_surrounded_chars(string): new_string = "" in_star = False for char in string: if char == '*': in_star = not in_star elif not in_star: new_string += char return new_string def input_modifier(string): """ This function is applied to your text inputs before they are fed into the model. """ return string def output_modifier(string): """ This function is applied to the model outputs. """ global wav_idx, model, current_params for i in params: if params[i] != current_params[i]: model = load_model() current_params = params.copy() break if params['activate'] == False: return string string = remove_surrounded_chars(string) string = string.replace('"', '') string = string.replace('“', '') string = string.replace('\n', ' ') string = string.strip() if string == '': string = 'empty reply, try regenerating' output_file = Path(f'extensions/silero_tts/outputs/{wav_idx:06d}.wav') model.save_wav(text=string, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file)) string = f'' wav_idx += 1 return string def bot_prefix_modifier(string): """ This function is only applied in chat mode. It modifies the prefix text for the Bot and can be used to bias its behavior. """ return string def ui(): # Gradio elements activate = gr.Checkbox(value=params['activate'], label='Activate TTS') voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice') # Event functions to update the parameters in the backend activate.change(lambda x: params.update({"activate": x}), activate, None) voice.change(lambda x: params.update({"speaker": x}), voice, None)