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Small english translation tweaks (#308)

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* Update en_US.json

* Update en_US.json
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kalomaze 2023-05-18 22:32:50 -05:00 committed by GitHub
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i18n/en_US.json
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@ -9,20 +9,20 @@
"全流程结束！": "all processes have been completed!",
"本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>使用需遵守的协议-LICENSE.txt</b>.": "This software is open source under the MIT license, the author does not have any control over the software, and those who use the software and spread the sounds exported by the software are solely responsible. <br>If you do not agree with this clause, you cannot use or quote any codes and files in the software package. See root directory <b>Agreement-LICENSE.txt</b> for details.",
"模型推理": "Model inference",
"推理音色": "Inferencing timbre",
"刷新音色列表和索引路径": "Refresh timbre list and index path",
"卸载音色省显存": "Unload timbre to save GPU memory",
"推理音色": "Inferencing voice",
"刷新音色列表和索引路径": "Refresh voice list and index path",
"卸载音色省显存": "Unload voice to save GPU memory",
"请选择说话人id": "Please select a speaker id",
"男转女推荐+12key, 女转男推荐-12key, 如果音域爆炸导致音色失真也可以自己调整到合适音域. ": "It is recommended +12key for male to female conversion, and -12key for female to male conversion. If the sound range explodes and the timbre is distorted, you can also adjust it to the appropriate range by yourself. ",
"男转女推荐+12key, 女转男推荐-12key, 如果音域爆炸导致音色失真也可以自己调整到合适音域. ": "It is recommended +12key for male to female conversion, and -12key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself. ",
"变调(整数, 半音数量, 升八度12降八度-12)": "transpose(integer, number of semitones, octave sharp 12 octave flat -12)",
"输入待处理音频文件路径(默认是正确格式示例)": "Enter the path of the audio file to be processed (the default is the correct format example)",
"选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比": "Select the algorithm for pitch extraction. Use 'pm' to speed up for singing voices, or use 'harvest' for better low-pitched voices, but it is extremely slow.",
"选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比": "Select the algorithm for pitch extraction. Use 'pm' for fast conversions, or 'harvest' for better pitch accuracy, but with longer conversion times.",
">=3则使用对harvest音高识别的结果使用中值滤波，数值为滤波半径，使用可以削弱哑音": ">=3:using median filter for f0. The number is median filter radius.",
"特征检索库文件路径,为空则使用下拉的选择结果": "Feature index file path. If null, use dropdown result.",
"自动检测index路径,下拉式选择(dropdown)": "Auto detect index path in logs directory. Dropdown.",
"自动检测index路径,下拉式选择(dropdown)": "Auto detect index path in logs directory. Pick the matching file from the dropdown.",
"特征文件路径": "Feature file path",
"检索特征占比": "Search feature ratio",
"后处理重采样至最终采样率，0为不进行重采样": "Post resample the audio to the final sample rate. Default: don't use post resample.",
"后处理重采样至最终采样率，0为不进行重采样": "Resample the audio in post to a different sample rate. Default: don't use post resample.",
"输入源音量包络替换输出音量包络融合比例，越靠近1越使用输出包络": "Use volume envelope of input to mix or replace the volume envelope of output, the closer the rate is to 1, the more output envelope is used. Default 1 (don't mix input envelope)",
"F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调": "F0 curve file, optional, one pitch per line, instead of the default F0 and ups and downs",
"转换": "Convert",
@ -42,8 +42,8 @@
"step1: 填写实验配置. 实验数据放在logs下, 每个实验一个文件夹, 需手工输入实验名路径, 内含实验配置, 日志, 训练得到的模型文件. ": "step1: Fill in the experimental configuration. The experimental data is placed under logs, and each experiment has a folder. You need to manually enter the experimental name path, which contains the experimental configuration, logs, and model files obtained from training. ",
"输入实验名": "Input experiment name",
"目标采样率": "Target sample rate",
"模型是否带音高指导(唱歌一定要, 语音可以不要)": "Does the model have pitch guidance (singing must, voice can not.)",
"版本(目前仅40k支持了v2)": "model architecture version (Now v2 version only supports 40k sample rate for testing)",
"模型是否带音高指导(唱歌一定要, 语音可以不要)": "Does the model have pitch guidance (required for singing; optional for speech, but recommended)",
"版本(目前仅40k支持了v2)": "Model architecture version (v2 version only supports 40k sample rate for testing purposes)",
"提取音高和处理数据使用的CPU进程数": "Number of CPU threads to use for pitch extraction and dataset processing",
"step2a: 自动遍历训练文件夹下所有可解码成音频的文件并进行切片归一化, 在实验目录下生成2个wav文件夹; 暂时只支持单人训练. ": "step2a: Automatically traverse all files that can be decoded into audio in the training folder and perform slice normalization, and generate 2 wav folders in the experiment directory; only single-person training is supported for the time being. ",
"输入训练文件夹路径": "Input training folder path",
@ -52,7 +52,7 @@
"step2b: 使用CPU提取音高(如果模型带音高), 使用GPU提取特征(选择卡号)": "step2b: Use CPU to extract pitch (if the model has pitch), use GPU to extract features (select card number)",
"以-分隔输入使用的卡号, 例如 0-1-2 使用卡0和卡1和卡2": "Enter the card numbers used separated by -, for example 0-1-2 use card 0 and card 1 and card 2",
"显卡信息": "GPU information",
"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢": "Select pitch extraction algorithm: Use 'pm' for faster processing of singing voice, 'dio' for high-quality speech but slower processing, and 'harvest' for the best quality but slowest processing.",
"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢": "Select pitch extraction algorithm: Use 'pm' for fastest extraction but lower-quality speech, 'dio' for improved speech but slower extraction, and 'harvest' for the best quality but slowest extraction.",
"特征提取": "Feature extraction",
"step3: 填写训练设置, 开始训练模型和索引": "step3: Fill in the training settings, start training the model and index",
"保存频率save_every_epoch": "Save frequency (save_every_epoch)",
@ -61,7 +61,7 @@
"是否仅保存最新的ckpt文件以节省硬盘空间": "Whether to save only the latest ckpt file to save disk space",
"否": "no",
"是否缓存所有训练集至显存. 10min以下小数据可缓存以加速训练, 大数据缓存会炸显存也加不了多少速": "Whether to cache all training sets to video memory. Small data under 10 minutes can be cached to speed up training, and large data cache will blow up video memory and not increase the speed much",
"是否在每次保存时间点将最终小模型保存至weights文件夹": "Save extracted small model to weights dir when every 'save frequency'",
"是否在每次保存时间点将最终小模型保存至weights文件夹": "Save a small finished model to the weights dir for every 'save frequency' epoch",
"加载预训练底模G路径": "Load pre-trained base model G path.",
"加载预训练底模D路径": "Load pre-trained base model D path.",
"训练模型": "Train model.",