Mangio-RVC-Fork/i18n/en_US.json

{
    "很遗憾您这没有能用的显卡来支持您训练": "Unfortunately, you don't have a GPU to help you train",
    "是": "yes",
    "step1:正在处理数据": "step 1: processing data",
    "step2a:无需提取音高": "step 2a: skipped extracting pitch",
    "step2b:正在提取特征": "step 2b: extracting features",
    "step3a:正在训练模型": "step 3a: training the model",
    "训练结束, 您可查看控制台训练日志或实验文件夹下的train.log": "Training completed, you can view the training logs in the console or the train.log within the experiement folder",
    "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": "Refresh timbre list",
    "卸载音色省显存": "Unload timbre 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. ",
    "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.",
    "crepe_hop_length": "Crepe Hop Length (Only applies to crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.",
    "特征检索库文件路径": "Feature search database file path",
    "特征文件路径": "Feature file path",
    "检索特征占比": "Search feature ratio",
    "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",
    "输出信息": "Export message",
    "输出音频(右下角三个点,点了可以下载)": "Export audio (three dots in the lower right corner, click to download)",
    "批量转换, 输入待转换音频文件夹, 或上传多个音频文件, 在指定文件夹(默认opt)下输出转换的音频. ": "For batch conversion, input the audio folder to be converted, or upload multiple audio files, and output the converted audio in the specified folder (opt by default). ",
    "指定输出文件夹": "Specify output folder",
    "输入待处理音频文件夹路径(去文件管理器地址栏拷就行了)": "Enter the path of the audio folder to be processed (just go to the address bar of the file manager and copy it)",
    "也可批量输入音频文件, 二选一, 优先读文件夹": "You can also input audio files in batches, choose one of the two, and read the folder first",
    "伴奏人声分离": "Accompaniment and vocal separation",
    "人声伴奏分离批量处理, 使用UVR5模型. <br>不带和声用HP2, 带和声且提取的人声不需要和声用HP5<br>合格的文件夹路径格式举例: E:\\codes\\py39\\vits_vc_gpu\\白鹭霜华测试样例(去文件管理器地址栏拷就行了)": "Batch processing of vocal accompaniment separation, using UVR5 model. <br>Without harmony, use HP2, with harmony and extracted vocals do not need harmony, use HP5<br>Example of qualified folder path format: E:\\ codes\\py39\\vits_vc_gpu\\Egret Shuanghua test sample (just go to the address bar of the file manager and copy it)",
    "输入待处理音频文件夹路径": "Input audio folder path",
    "模型": "Model",
    "人声提取激进程度": "vocal extraction aggressiveness",
    "指定输出人声文件夹": "Specify vocals output folder",
    "指定输出乐器文件夹": "Specify instrumentals output folder",
    "训练": "Train",
    "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.)",
    "否": "no",
    "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",
    "请指定说话人id": "Please specify speaker ID",
    "处理数据": "Process data",
    "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",
    "提取音高使用的CPU进程数": "Number of CPU threads to use for pitch extraction",
    "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.",
    "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)",
    "总训练轮数total_epoch": "Total training epochs (total_epoch)",
    "每张显卡的batch_size": "batch_size for every GPU",
    "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",
    "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",
    "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.",
    "训练特征索引": "Train feature index.",
    "一键训练": "One-click training.",
    "ckpt处理": "ckpt processing.",
    "模型融合, 可用于测试音色融合": "Model Fusion, which can be used to test sound fusion",
    "A模型路径": "A model path.",
    "B模型路径": "B model path.",
    "A模型权重": "A model weight for model A.",
    "模型是否带音高指导": "Whether the model has pitch guidance.",
    "要置入的模型信息": "Model information to be placed.",
    "保存的模型名不带后缀": "Saved model name without extension.",
    "融合": "Fusion.",
    "修改模型信息(仅支持weights文件夹下提取的小模型文件)": "Modify model information (only small model files extracted from the weights folder are supported)",
    "模型路径": "Model path",
    "要改的模型信息": "Model information to be modified",
    "保存的文件名, 默认空为和源文件同名": "The saved file name, the default is empty and the same name as the source file",
    "修改": "Modify",
    "查看模型信息(仅支持weights文件夹下提取的小模型文件)": "View model information (only small model files extracted from the weights folder are supported)",
    "查看": "View",
    "模型提取(输入logs文件夹下大文件模型路径),适用于训一半不想训了模型没有自动提取保存小文件模型,或者想测试中间模型的情况": "Model extraction (enter the path of the large file model under the logs folder), which is suitable for half of the training and does not want to train the model without automatically extracting and saving the small file model, or if you want to test the intermediate model",
    "保存名": "Save Name",
    "模型是否带音高指导,1是0否": "Whether the model has pitch guidance, 1 for yes, 0 for no",
    "提取": "Extract",
    "Onnx导出": "Export Onnx",
    "RVC模型路径": "RVC Model Path",
    "Onnx输出路径": "Onnx Export Path",
    "MoeVS模型": "MoeVS Model",
    "导出Onnx模型": "Export Onnx Model",
    "招募音高曲线前端编辑器": "Recruit front-end editors for pitch curves",
    "加开发群联系我xxxxx": "Add development group to contact me xxxxx",
    "点击查看交流、问题反馈群号": "Click to view the communication and problem feedback group number",
    "xxxxx": "xxxxx",
    "加载模型": "load model",
    "Hubert模型": "Hubert File",
    "选择.pth文件": "Select the .pth file",
    "选择.index文件": "Select the .index file",
    "选择.npy文件": "Select the .npy file",
    "输入设备": "input device",
    "输出设备": "output device",
    "音频设备(请使用同种类驱动)": "Audio device (please use the same type of driver)",
    "响应阈值": "response threshold",
    "音调设置": "tone setting",
    "Index Rate": "Index Rate",
    "常规设置": "general settings",
    "采样长度": "Sample length",
    "淡入淡出长度": "fade length",
    "额外推理时长": "extra inference time",
    "输入降噪": "Input Noise Reduction",
    "输出降噪": "Output Noise Reduction",
    "性能设置": "performance settings",
    "开始音频转换": "start audio conversion",
    "停止音频转换": "stop audio conversion",
    "推理时间(ms):": "Infer Time(ms):"
}