Merge pull request #38 from XiuChen-Liu/main

更新 README

README-CN.md

@@ -34,6 +34,8 @@
 可以传入参数 --dataset `{dataset}` 支持 adatatang_200zh, magicdata
 > 假如你下载的 `aidatatang_200zh`文件放在D盘，`train`文件路径为 `D:\data\aidatatang_200zh\corpus\train` , 你的`datasets_root`就是 `D:\data\`
 
+>假如發生 `頁面文件太小，無法完成操作`，請參考這篇[文章](https://blog.csdn.net/qq_17755303/article/details/112564030)，將虛擬內存更改為100G(102400)，例如:档案放置D槽就更改D槽的虚拟内存
+
 * 预处理嵌入：
 `python synthesizer_preprocess_embeds.py <datasets_root>/SV2TTS/synthesizer`
 

README.md

@@ -27,12 +27,16 @@
 > If you get an `ERROR: Could not find a version that satisfies the requirement torch==1.9.0+cu102 (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2 )` This error is probably due to a low version of python, try using 3.9 and it will install successfully
 * Install [ffmpeg](https://ffmpeg.org/download.html#get-packages).
 * Run `pip install -r requirements.txt` to install the remaining necessary packages.
+* Install webrtcvad `pip install webrtcvad-wheels`(If you need)
 > Note that we are using the pretrained encoder/vocoder but synthesizer, since the original model is incompatible with the Chinese sympols. It means the demo_cli is not working at this moment.
 ### 2. Train synthesizer with your dataset
 * Download aidatatang_200zh or SLR68 dataset and unzip: make sure you can access all .wav in *train* folder
 * Preprocess with the audios and the mel spectrograms:
 `python synthesizer_preprocess_audio.py <datasets_root>`
 Allow parameter `--dataset {dataset}` to support adatatang_200zh, magicdata
+
+>If it happens `the page file is too small to complete the operation`, please refer to this [video](https://www.youtube.com/watch?v=Oh6dga-Oy10&ab_channel=CodeProf) and change the virtual memory to 100G (102400), for example : When the file is placed in the D disk, the virtual memory of the D disk is changed.
+
 * Preprocess the embeddings:
 `python synthesizer_preprocess_embeds.py <datasets_root>/SV2TTS/synthesizer`