| import warnings | |
| warnings.filterwarnings("ignore") | |
| # 外部库 | |
| import re | |
| import requests | |
| import argparse | |
| import json | |
| import os | |
| import re | |
| import tempfile | |
| import librosa | |
| import numpy as np | |
| # import torch | |
| # from torch import no_grad, LongTensor | |
| # import commons | |
| import gradio as gr | |
| import gradio.utils as gr_utils | |
| import gradio.processing_utils as gr_processing_utils | |
| # 内部库 | |
| # from models import SynthesizerTrn | |
| # from text import text_to_sequence, text_to_sequence_for_test, _clean_text | |
| # from mel_processing import spectrogram_torch | |
| # import utils | |
| # from text.symbols import symbols | |
| all_example = "my voice is my passport verify me." | |
| eleven_voice_id = [ | |
| "21m00Tcm4TlvDq8ikWAM", | |
| "29vD33N1CtxCmqQRPOHJ", | |
| "2EiwWnXFnvU5JabPnv8n", | |
| "5Q0t7uMcjvnagumLfvZi", | |
| "AZnzlk1XvdvUeBnXmlld", | |
| "CYw3kZ02Hs0563khs1Fj", | |
| "D38z5RcWu1voky8WS1ja", | |
| "EXAVITQu4vr4xnSDxMaL", | |
| "ErXwobaYiN019PkySvjV", | |
| "GBv7mTt0atIp3Br8iCZE", | |
| "IKne3meq5aSn9XLyUdCD", | |
| "JBFqnCBsd6RMkjVDRZzb", | |
| "LcfcDJNUP1GQjkzn1xUU", | |
| "MF3mGyEYCl7XYWbV9V6O", | |
| "N2lVS1w4EtoT3dr4eOWO", | |
| "ODq5zmih8GrVes37Dizd", | |
| "SOYHLrjzK2X1ezoPC6cr", | |
| "TX3LPaxmHKxFdv7VOQHJ", | |
| "ThT5KcBeYPX3keUQqHPh", | |
| "TxGEqnHWrfWFTfGW9XjX", | |
| "VR6AewLTigWG4xSOukaG", | |
| "XB0fDUnXU5powFXDhCwa", | |
| "Xb7hH8MSUJpSbSDYk0k2", | |
| "XrExE9yKIg1WjnnlVkGX", | |
| "ZQe5CZNOzWyzPSCn5a3c", | |
| "Zlb1dXrM653N07WRdFW3", | |
| "bVMeCyTHy58xNoL34h3p", | |
| "flq6f7yk4E4fJM5XTYuZ", | |
| "g5CIjZEefAph4nQFvHAz", | |
| "iP95p4xoKVk53GoZ742B", | |
| "jBpfuIE2acCO8z3wKNLl", | |
| "jsCqWAovK2LkecY7zXl4", | |
| "nPczCjzI2devNBz1zQrb", | |
| "oWAxZDx7w5VEj9dCyTzz", | |
| "onwK4e9ZLuTAKqWW03F9", | |
| "pFZP5JQG7iQjIQuC4Bku", | |
| "pMsXgVXv3BLzUgSXRplE", | |
| "pNInz6obpgDQGcFmaJgB", | |
| "piTKgcLEGmPE4e6mEKli", | |
| "pqHfZKP75CvOlQylNhV4", | |
| "t0jbNlBVZ17f02VDIeMI", | |
| "yoZ06aMxZJJ28mfd3POQ", | |
| "z9fAnlkpzviPz146aGWa", | |
| "zcAOhNBS3c14rBihAFp1", | |
| "zrHiDhphv9ZnVXBqCLjz", | |
| ] | |
| eleven_name = [ | |
| "Rachel", | |
| "Drew", | |
| "Clyde", | |
| "Paul", | |
| "Domi", | |
| "Dave", | |
| "Fin", | |
| "Sarah", | |
| "Antoni", | |
| "Thomas", | |
| "Charlie", | |
| "George", | |
| "Emily", | |
| "Elli", | |
| "Callum", | |
| "Patrick", | |
| "Harry", | |
| "Liam", | |
| "Dorothy", | |
| "Josh", | |
| "Arnold", | |
| "Charlotte", | |
| "Alice", | |
| "Matilda", | |
| "James", | |
| "Joseph", | |
| "Jeremy", | |
| "Michael", | |
| "Ethan", | |
| "Chris", | |
| "Gigi", | |
| "Freya", | |
| "Brian", | |
| "Grace", | |
| "Daniel", | |
| "Lily", | |
| "Serena", | |
| "Adam", | |
| "Nicole", | |
| "Bill", | |
| "Jessie", | |
| "Sam", | |
| "Glinda", | |
| "Giovanni", | |
| "Mimi", | |
| ] | |
| eleven_id_model_name_dict = dict(zip(eleven_name, eleven_voice_id)) | |
| def openai(text, name): | |
| headers = { | |
| 'Authorization': 'Bearer ' + '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', | |
| 'Content-Type': 'application/json', | |
| } | |
| json_data = { | |
| 'model': 'tts-1-hd', | |
| 'input': f'{text}', | |
| 'voice': f'{name}', | |
| } | |
| response = requests.post('https://api.openai.com/v1/audio/speech', headers=headers, json=json_data) | |
| # Note: json_data will not be serialized by requests | |
| # exactly as it was in the original request. | |
| #data = '{\n "model": "tts-1",\n "input": "The quick brown fox jumped over the lazy dog.",\n "voice": "alloy"\n }' | |
| #response = requests.post('https://api.openai.com/v1/audio/speech', headers=headers, data=data) | |
| return "Success", response | |
| def elevenlabs(text,name): | |
| url = f"https://api.elevenlabs.io/v1/text-to-speech/{name}" | |
| CHUNK_SIZE = 1024 | |
| #url = "https://api.elevenlabs.io/v1/text-to-speech/<voice-id>" | |
| headers = { | |
| "Accept": "audio/mpeg", | |
| "Content-Type": "application/json", | |
| "xi-api-key": "a3391f0e3ff8472b61978dbb70ccc6fe" | |
| } | |
| data = { | |
| "text": f"{text}", | |
| "model_id": "eleven_monolingual_v1", | |
| "voice_settings": { | |
| "stability": 0.5, | |
| "similarity_boost": 0.5 | |
| } | |
| } | |
| response = requests.post(url, json=data, headers=headers) | |
| # with open('output.mp3', 'wb') as f: | |
| # for chunk in response.iter_content(chunk_size=CHUNK_SIZE): | |
| # if chunk: | |
| # f.write(chunk) | |
| return "Success", response | |
| microsoft_model_list = [ | |
| "en-US-AvaMultilingualNeural" | |
| ] | |
| def microsoft(text, name, style="Neural"): | |
| """ | |
| :param text: | |
| :param name: | |
| :param style: | |
| :return: | |
| """ | |
| headers = { | |
| 'Ocp-Apim-Subscription-Key': '1f1ef0ce53b84261be94fab81df7e628', | |
| 'Content-Type': 'application/ssml+xml', | |
| 'X-Microsoft-OutputFormat': 'audio-16khz-128kbitrate-mono-mp3', | |
| 'User-Agent': 'curl', | |
| } | |
| data = ("<speak version='1.0' xml:lang='en-US'>" | |
| f"<voice xml:lang='en-US' name='{name}'>" # xml:gender='Female' | |
| f"{text}" | |
| "</voice>" | |
| "</speak>") | |
| response = requests.post( | |
| 'https://japaneast.tts.speech.microsoft.com/cognitiveservices/v1', | |
| headers=headers, | |
| data=data, | |
| ) | |
| # data = { | |
| # "text":text, | |
| # "name":name, | |
| # "style":style, | |
| # "format":"mp3"} | |
| # audio_url = requests.get(microsoft_url, headers=microsoft_headers, json=data).json()['data']['url'] | |
| return "Success", response | |
| # def google(text,name): | |
| # # import subprocess | |
| # # command1 = subprocess.run('gcloud auth print-access-token', shell=True, capture_output=True, text=True).stdout | |
| # headers = { | |
| # 'Authorization': 'Bearer ' + "synclub-2383kjhjksxfv.2341gs", | |
| # 'x-goog-user-project': 'PROJECT_ID', | |
| # 'Content-Type': 'application/json; charset=utf-8', | |
| # } | |
| # data = { | |
| # "input": { | |
| # "text": f"{text}"}, | |
| # "voice": { | |
| # "languageCode": "en-gb", | |
| # "name": "en-GB-Standard-A", | |
| # "ssmlGender": "FEMALE" | |
| # }, | |
| # "audioConfig": { | |
| # "audioEncoding": "MP3" | |
| # } | |
| # } | |
| # response = requests.post('https://texttospeech.googleapis.com/v1/text:synthesize', headers=headers, data=data) | |
| # return "Success", response | |
| if __name__ == '__main__': | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--device', type=str, default='cuda') | |
| parser.add_argument("--share", action="store_true", default=True, help="share gradio app") | |
| parser.add_argument("--port", type=int, default=8081, help="port") | |
| parser.add_argument('--model_info_path', type=str, default='/gluster/speech_data/info.json') | |
| args = parser.parse_args() | |
| # app = gr.Blocks() | |
| # with app: | |
| # gr.Markdown("## Japanese TTS Demo") | |
| # with gr.Tabs(): | |
| # with gr.TabItem("微软"): | |
| # tts_input1 = gr.TextArea(label="Text", value=all_example) | |
| # tts_input2 = gr.Dropdown(microsoft_model_list, label="name") | |
| # tts_submit = gr.Button("Generate", variant="primary") | |
| # tts_output1 = gr.Textbox(label="Output Message") | |
| # tts_output2 = gr.Audio(label="Output Audio") | |
| # tts_submit.click(microsoft, [tts_input1, tts_input2], | |
| # [tts_output1, tts_output2]) | |
| # _, audio = microsoft(all_example, 'en-US-AvaMultilingualNeural') | |
| # _, audio = google(all_example,'alloy') | |
| # print(audio) | |
| # with open("test4.mp3", "wb") as f: | |
| # f.write(audio.content) | |
| #_, audio = elevenlabs(all_example, "21m00Tcm4TlvDq8ikWAM") | |
| # print(audio) | |
| # with open('output.mp3', 'wb') as f: | |
| # for chunk in audio.iter_content(chunk_size=1024): | |
| # if chunk: | |
| # f.write(chunk) | |
| # device = torch.device(args.device) | |
| # models_tts = [] | |
| # with open(args.model_info_path, "r", encoding="utf-8") as f: | |
| # models_info = json.load(f) | |
| # for i, info in models_info.items(): | |
| # model_name = info["model_name"] | |
| # author = info["author"] | |
| # lang = info["lang"] | |
| # example = info["example"] | |
| # config_path = info["config_path"] | |
| # model_path = info["model_path"] | |
| # model_type = info["model_type"] | |
| # hps = utils.get_hparams_from_file(config_path) | |
| # if model_type == "vits": | |
| # emotion_type = None | |
| # elif model_type == "vits-emotion": | |
| # emotion_type = "embedding" | |
| # elif model_type == "vits-emotion-logits": | |
| # emotion_type = "logits" | |
| # model = SynthesizerTrn( | |
| # len(symbols), | |
| # hps.data.filter_length // 2 + 1, | |
| # hps.train.segment_size // hps.data.hop_length, | |
| # emotion_type=emotion_type, | |
| # **hps.model) | |
| # utils.load_checkpoint(model_path, model, None) | |
| # model.eval().to(device) | |
| # if model_type == "vits": | |
| # # 普通TTS | |
| # models_tts.append((model_name, author, lang, example, create_tts_fn(model, hps))) | |
| app = gr.Blocks() | |
| with app: | |
| gr.Markdown("## Japanese TTS Demo") | |
| with gr.Tabs(): | |
| # with gr.TabItem("自研"): | |
| # with gr.Tabs(): | |
| # for i, (model_name, author, lang, example, tts_fn) in enumerate(models_tts): | |
| # with gr.TabItem(model_name): | |
| # with gr.Column(): | |
| # tts_input1 = gr.TextArea(label="Text", value=example) | |
| # tts_input2 = gr.Slider(label="Speed", value=1.0, minimum=0.4, maximum=3, step=0.1) | |
| # tts_input3 = gr.Slider(label="noise_scale", value=0.0, minimum=0.0, maximum=2, step=0.1) | |
| # tts_input4 = gr.Slider(label="noise_scale_w", value=0.0, | |
| # minimum=0.0, maximum=2, step=0.1) | |
| # tts_input5 = gr.Slider(label="volume", value=1.0, minimum=0.1, maximum=4, step=0.1) | |
| # tts_submit = gr.Button("Generate", variant="primary") | |
| # tts_output1 = gr.Textbox(label="Output Message") | |
| # tts_output2 = gr.Audio(label="Output Audio") | |
| # tts_submit.click(tts_fn, [tts_input1, tts_input2, tts_input3, tts_input4, tts_input5], | |
| # [tts_output1, tts_output2]) | |
| # with gr.TabItem("谷歌"): | |
| # tts_input1 = gr.TextArea(label="Text", value=all_example) | |
| # tts_input2 = gr.Dropdown(google_model_list, label="name") | |
| # tts_submit = gr.Button("Generate", variant="primary") | |
| # tts_output1 = gr.Textbox(label="Output Message") | |
| # tts_output2 = gr.Audio(label="Output Audio") | |
| # tts_submit.click(google, [tts_input1, tts_input2], | |
| # [tts_output1, tts_output2]) | |
| with gr.TabItem("微软"): | |
| tts_input1 = gr.TextArea(label="Text", value=all_example) | |
| tts_input2 = gr.Dropdown(microsoft_model_list, label="name") | |
| tts_submit = gr.Button("Generate", variant="primary") | |
| tts_output1 = gr.Textbox(label="Output Message") | |
| tts_output2 = gr.Audio(label="Output Audio") | |
| tts_submit.click(microsoft, [tts_input1, tts_input2], | |
| [tts_output1, tts_output2]) | |
| # with gr.TabItem("coefont"): | |
| # tts_input1 = gr.TextArea(label="Text", value=all_example) | |
| # tts_input2 = gr.Dropdown(coefont_model_list, label="name") | |
| # tts_submit = gr.Button("Generate", variant="primary") | |
| # tts_output1 = gr.Textbox(label="Output Message") | |
| # tts_output2 = gr.Audio(label="Output Audio") | |
| # tts_submit.click(coefont, [tts_input1, tts_input2], | |
| # [tts_output1, tts_output2]) | |
| app.launch(show_api=False, | |
| share=args.share, | |
| server_name='0.0.0.0', | |
| server_port=args.port, | |
| show_error=True) | |