forked from killua/TakwayPlatform
215 lines
9.3 KiB
Plaintext
215 lines
9.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Importing the dtw module. When using in academic works please cite:\n",
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" T. Giorgino. Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package.\n",
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" J. Stat. Soft., doi:10.18637/jss.v031.i07.\n",
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"\n"
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]
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}
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],
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"source": [
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"import sys\n",
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"import os\n",
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"sys.path.append(\"../\")\n",
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"from utils.tts.openvoice_utils import TextToSpeech\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\utils\\weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
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" warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
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"Building prefix dict from the default dictionary ...\n",
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"Loading model from cache C:\\Users\\bing\\AppData\\Local\\Temp\\jieba.cache\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"load base tts model successfully!\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Loading model cost 0.304 seconds.\n",
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"Prefix dict has been built successfully.\n",
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"Some weights of the model checkpoint at bert-base-multilingual-uncased were not used when initializing BertForMaskedLM: ['cls.seq_relationship.bias', 'cls.seq_relationship.weight']\n",
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"- This IS expected if you are initializing BertForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
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"- This IS NOT expected if you are initializing BertForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\modules\\conv.py:797: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\cudnn\\Conv_v8.cpp:919.)\n",
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" return F.conv_transpose1d(\n",
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\modules\\conv.py:306: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\cudnn\\Conv_v8.cpp:919.)\n",
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" return F.conv1d(input, weight, bias, self.stride,\n",
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\utils\\weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
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" warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"generate base speech!\n",
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"**********************,tts sr 44100\n",
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"audio segment length is [torch.Size([81565])]\n",
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"True\n",
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"Loaded checkpoint 'D:\\python\\OpenVoice\\checkpoints_v2\\converter/checkpoint.pth'\n",
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"missing/unexpected keys: [] []\n",
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"load tone color converter successfully!\n"
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]
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}
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],
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"source": [
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"model = TextToSpeech(use_tone_convert=True, device=\"cuda\", debug=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"# 测试用，将mp3转为int32类型的numpy，对齐输入端\n",
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"from pydub import AudioSegment\n",
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"import numpy as np\n",
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"source_audio=r\"D:\\python\\OpenVoice\\resources\\demo_speaker0.mp3\"\n",
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"audio = AudioSegment.from_file(source_audio, format=\"mp3\")\n",
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"raw_data = audio.raw_data\n",
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"audio_array = np.frombuffer(raw_data, dtype=np.int32)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"OpenVoice version: v2\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\functional.py:665: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
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"Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\SpectralOps.cpp:878.)\n",
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" return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]\n",
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\modules\\conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\cudnn\\Conv_v8.cpp:919.)\n",
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" return F.conv2d(input, weight, bias, self.stride,\n"
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]
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}
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],
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"source": [
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"# 获取并设置目标说话人的speaker embedding\n",
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"# audio_array ：输入的音频信号，类型为 np.ndarray\n",
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"# 获取speaker embedding\n",
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"target_se = model.audio2emb(audio_array, rate=44100, vad=True)\n",
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"# 将模型的默认目标说话人embedding设置为 target_se\n",
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"model.initialize_target_se(target_se)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\modules\\conv.py:797: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\cudnn\\Conv_v8.cpp:919.)\n",
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" return F.conv_transpose1d(\n",
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"c:\\Users\\bing\\.conda\\envs\\openVoice\\lib\\site-packages\\torch\\nn\\modules\\conv.py:306: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\cudnn\\Conv_v8.cpp:919.)\n",
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" return F.conv1d(input, weight, bias, self.stride,\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"generate base speech!\n",
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"**********************,tts sr 44100\n",
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"audio segment length is [torch.Size([216378])]\n",
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"Audio saved to D:\\python\\OpenVoice\\outputs_v2\\demo_tts.wav\n"
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]
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}
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],
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"source": [
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"# 测试base_tts，不含音色转换\n",
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"text = \"你好呀,我不知道该怎么告诉你这件事，但是我真的很需要你。\"\n",
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"audio, sr = model._base_tts(text, speed=1)\n",
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"audio = model.tensor2numpy(audio)\n",
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"model.save_audio(audio, sr, r\"D:\\python\\OpenVoice\\outputs_v2\\demo_tts.wav\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"generate base speech!\n",
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"**********************,tts sr 44100\n",
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"audio segment length is [torch.Size([216378])]\n",
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"torch.float32\n",
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"**********************************, convert sr 22050\n",
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"tone color has been converted!\n",
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"Audio saved to D:\\python\\OpenVoice\\outputs_v2\\demo.wav\n"
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]
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}
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],
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"source": [
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"# 测试整体pipeline，包含音色转换\n",
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"text = \"你好呀,我不知道该怎么告诉你这件事，但是我真的很需要你。\"\n",
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"audio_bytes, sr = model.tts(text, speed=1)\n",
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"audio = np.frombuffer(audio_bytes, dtype=np.int16).flatten()\n",
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"model.save_audio(audio, sr, r\"D:\\python\\OpenVoice\\outputs_v2\\demo.wav\" )"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "openVoice",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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