Retrieval-based-Voice-Conversion-WebUI/i18n/locale/en_US.json

{
    "%s运行中，请先停止该任务": "%s is running; stop it before starting another task",
    "====> 轮次：{} {}": "====> Epoch: {} {}",
    "A模型权重": "Weight (w) for Model A:",
    "A模型路径": "Path to Model A:",
    "B模型路径": "Path to Model B:",
    "CUDA Graph预热完成": "CUDA Graph warm-up complete",
    "CUDA可用：%s": "CUDA available: %s",
    "输入训练文件夹路径，例如：E:\\我的训练集": "Training folder path, for example: E:\\My training set",
    "F0与HuBERT特征提取": "F0 and HuBERT feature extraction",
    "F0提取": "F0 extraction",
    "F0提取没有生成有效结果，已停止训练": "F0 extraction produced no valid results. Training has been stopped.",
    "HuBERT特征": "HuBERT features",
    "HuBERT特征提取没有生成有效结果，已停止训练": "HuBERT feature extraction produced no valid results. Training has been stopped.",
    "Index Rate": "Index Rate",
    "SOLA偏移：%d": "SOLA offset: %d",
    "[F0提取] 完成 | 成功：%s | 跳过：%s | 失败：%s": "[F0 extraction] Completed | Success: %s | Skipped: %s | Failed: %s",
    "[F0提取] 待处理：%s": "[F0 extraction] Pending: %s",
    "[F0提取] 无待处理音频，已全部跳过": "[F0 extraction] No pending audio; all files were skipped",
    "[F0提取] 进度：%s/%s | 成功：%s | 跳过：%s | %s": "[F0 extraction] Progress: %s/%s | Success: %s | Skipped: %s | %s",
    "[F0提取][失败] %s": "[F0 extraction][Failed] %s",
    "[F0提取][失败] %s\n%s": "[F0 extraction][Failed] %s\n%s",
    "[HuBERT特征] 完成 | 成功：%s | 跳过：%s | 失败：%s": "[HuBERT features] Completed | Success: %s | Skipped: %s | Failed: %s",
    "[HuBERT特征] 无待处理音频，已全部跳过：%s": "[HuBERT features] No pending audio; skipped: %s",
    "[HuBERT特征] 正在加载模型：%s": "[HuBERT features] Loading model: %s",
    "[HuBERT特征] 设备：%s | 待处理：%s | 已跳过：%s": "[HuBERT features] Device: %s | Pending: %s | Skipped: %s",
    "[HuBERT特征] 进度：%s/%s | 成功：%s | 失败：%s | %s | %s": "[HuBERT features] Progress: %s/%s | Success: %s | Failed: %s | %s | %s",
    "[HuBERT特征][失败] %s\n%s": "[HuBERT features][Failed] %s\n%s",
    "[HuBERT特征][失败] %s 包含NaN": "[HuBERT features][Failed] %s contains NaN values",
    "[HuBERT特征][失败] 模型不存在：%s": "[HuBERT features][Failed] Model not found: %s",
    "[数据切分] 多说话人待处理：%s | 进程数：%s": "[Dataset preprocessing] Multi-speaker files: %s | Workers: %s",
    "[数据切分] 子任务完成 | 成功：%s | 失败：%s": "[Data slicing] Worker completed | Success: %s | Failed: %s",
    "[数据切分] 完成": "[Data slicing] Completed",
    "[数据切分] 开始": "[Data slicing] Started",
    "[数据切分] 待处理：%s | 进程数：%s": "[Data slicing] Pending: %s | Processes: %s",
    "[数据切分] 进度：%s/%s | %s": "[Data slicing] Progress: %s/%s | %s",
    "[数据切分][失败] %s": "[Data slicing][Failed] %s",
    "[数据切分][失败] %s\n%s": "[Data slicing][Failed] %s\n%s",
    "[数据切分][跳过] 无效或异常音频片段：%s_%s | 峰值：%s": "[Data slicing][Skipped] Invalid or abnormal audio segment: %s_%s | Peak: %s",
    "[索引训练] 写入进度：%s/%s": "[Index training] Write progress: %s/%s",
    "[索引训练] 外部索引链接已存在：%s": "[Index training] External index link already exists: %s",
    "[索引训练] 已链接索引到外部目录：%s": "[Index training] Linked index to external directory: %s",
    "[索引训练] 成功构建索引：%s": "[Index training] Index built successfully: %s",
    "[索引训练] 正在写入特征向量": "[Index training] Adding feature vectors",
    "[索引训练] 正在将%s条特征聚类为10000个中心": "[Index training] Clustering %s feature vectors into 10,000 centers",
    "[索引训练] 正在训练索引": "[Index training] Training index",
    "[索引训练] 特征形状：%s | IVF数量：%s": "[Index training] Feature shape: %s | IVF count: %s",
    "[索引训练][失败] 无法链接索引到外部目录：%s\n%s": "[Index training][Failed] Could not link index to external directory: %s\n%s",
    "[索引训练][失败] 聚类失败，将使用原始特征继续\n%s": "[Index training][Failed] Clustering failed; continuing with the original features\n%s",
    "[索引训练][失败] 请先进行特征提取": "[Index training][Failed] Extract features first",
    "[索引训练][跳过] added索引已存在：%s": "[Index training][Skipped] added index already exists: %s",
    "[索引训练][跳过] trained索引已存在：%s": "[Index training][Skipped] trained index already exists: %s",
    "ckpt处理": "ckpt Processing",
    "hubert: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": "HuBERT: Enter GPU IDs separated by hyphens; for example, 0-1-2 uses GPUs 0, 1, and 2",
    "index文件路径不可包含中文": "The index file path cannot contain Chinese characters",
    "pth文件路径不可包含中文": "The .pth file path cannot contain Chinese characters",
    "rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程": "Enter the GPU index(es) separated by '-', e.g., 0-0-1 to use 2 processes in GPU0 and 1 process in GPU1",
    "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. ": "Step 1: Fill in the experimental configuration. Experimental data is stored in the 'logs' folder, with each experiment having a separate folder. Manually enter the experiment name path, which contains the experimental configuration, logs, and trained model files.",
    "step2a: 扫描训练音频并进行切片归一化，在实验目录下生成训练wav文件。": "Step 2a: Scan, slice, and normalize training audio, then create training WAV files in the experiment directory.",
    "step2b: 音高与hubert语义特征提取": "Step 2b: Pitch and HuBERT semantic feature extraction",
    "step3: 填写训练设置, 开始训练模型和索引": "Step 3: Fill in the training settings and start training the model and index",
    "……仅显示最近10条失败记录": "…Showing only the 10 most recent failures",
    "……已省略前%s行，仅显示最新状态": "…Omitted the first %s lines; showing the latest status only",
    "一键训练": "One-click training",
    "上一页": "Previous",
    "下一页": "Next",
    "为多说话人训练集建立清单。空行会被忽略；路径、说话人名称、说话人ID或重复次数填写不全的行会在提交时提示。": "Create a multi-speaker dataset manifest. Empty rows are ignored; incomplete path, speaker name, speaker ID, or repeat count fields are reported on submission.",
    "主结果文件夹": "Primary output folder",
    "也可批量输入音频文件, 二选一, 优先读文件夹": "Multiple audio files can also be imported. If a folder path exists, this input is ignored.",
    "人声、伴奏与混响批量处理，使用pymss/MSST模型。": "Batch processing of vocals, accompaniment, and reverb using pymss/MSST models.",
    "人声伴奏分离&去混响": "Vocals/Accompaniment Separation & Dereverberation",
    "仅支持pm和rmvpe音高提取算法": "Only the pm and rmvpe pitch extraction methods are supported",
    "从训练检查点提取的模型": "Model extracted from a training checkpoint",
    "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 GPU index(es) separated by '-', e.g., 0-1-2 to use GPU 0, 1, and 2:",
    "以下行填写不完整或无效，已忽略：%s": "The following incomplete or invalid rows were ignored: %s",
    "任务": "Task",
    "使用显卡：%s": "GPUs in use: %s",
    "使用模型采样率": "Use model sample rate",
    "使用设备采样率": "Use device sample rate",
    "保存名": "Save name:",
    "保存的文件名, 默认空为和源文件同名": "Save file name (default: same as the source file):",
    "保存的模型名不带后缀": "Saved model name (without extension):",
    "保存频率save_every_epoch": "Save frequency (save_every_epoch):",
    "保护清辅音和呼吸声，防止电音撕裂等artifact，拉满0.5不开启，调低加大保护力度但可能降低索引效果": "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:",
    "修改": "Modify",
    "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 supported for small model files extracted from the 'weights' folder)",
    "停止一键训练": "Stop one-click training",
    "停止分离": "Stop separation",
    "停止处理数据": "Stop data preprocessing",
    "停止特征提取": "Stop feature extraction",
    "停止训练模型": "Stop model training",
    "停止训练索引": "Stop index training",
    "停止音频转换": "Stop audio conversion",
    "分离残余文件夹": "Residual output folder",
    "删除末行": "Remove last row",
    "判别器预训练模型不存在，将不使用：assets/pretrained%s/%sD%s.pth": "Discriminator pretrained model not found; it will not be used: assets/pretrained%s/%sD%s.pth",
    "刷新音色列表": "Refresh voice list",
    "加载模型": "Load model",
    "加载预训练底模D路径": "Load pre-trained base model D path:",
    "加载预训练底模G路径": "Load pre-trained base model G path:",
    "单次推理": "Single Inference",
    "单说话人": "Single speaker",
    "卸载音色省显存": "Unload voice to save GPU memory:",
    "变调(整数, 半音数量, 升八度12降八度-12)": "Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):",
    "合成": "Synthesis",
    "后处理重采样至最终采样率，0为不进行重采样": "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:",
    "否": "No",
    "响应阈值": "Response threshold",
    "响度因子": "loudness factor",
    "处理中": "Processing",
    "处理数据": "Process data",
    "处理方式": "Processing mode",
    "多说话人": "Multiple speakers",
    "注意：多说话人训练音色还原度不一定有单说话人分开训练好！": "Note: Multi-speaker training may not reproduce each voice as accurately as training each speaker separately!",
    "多说话人子文件夹无效（格式应为名称_ID_重复次数、ID为0~109、重复次数为正整数、同一ID的名称需一致且目录需有音频）：%s": "Invalid multi-speaker subfolders (expected Name_ID_Repeat, ID 0-109, a positive repeat count, one consistent name per ID, and at least one audio file): %s",
    "多说话人总文件夹只扫描根目录下的直接子文件夹，根目录文件会被忽略。\n子文件夹必须命名为x_y_z：x是说话人名称，y是说话人ID（0~109，共110个），z是训练集重复次数。\n也可以到右侧“多说话人训练集辅助”编辑并提交训练集清单。": "Only direct subfolders of the multi-speaker root are scanned; root files are ignored.\nName each subfolder x_y_z: x is the speaker name, y is the speaker ID (0-109, 110 choices), and z is the repeat count.\nYou can also submit a manifest from the Multi-speaker Dataset Helper tab.",
    "多说话人训练集总文件夹不存在：%s": "Multi-speaker dataset root does not exist: %s",
    "多说话人训练集总文件夹中没有有效音频": "The multi-speaker dataset root contains no valid audio",
    "多说话人训练集总文件夹中没有直接子文件夹": "The multi-speaker dataset root has no direct subfolders",
    "多说话人训练集总文件夹路径": "Multi-speaker dataset root",
    "多说话人训练集清单不存在，请先提交辅助清单或填写总文件夹": "The multi-speaker manifest does not exist. Submit it from the helper tab or enter a dataset root first",
    "多说话人训练集清单包含无效条目：%s": "The multi-speaker manifest contains an invalid entry: %s",
    "多说话人训练集清单存在重复输出标识：%s": "The multi-speaker manifest contains a duplicate output key: %s",
    "多说话人训练集清单已保存：%s；有效音频%s个": "Multi-speaker dataset manifest saved: %s; valid audio files: %s",
    "多说话人训练集清单格式错误": "The multi-speaker manifest format is invalid",
    "多说话人训练集清单没有有效音频": "The multi-speaker manifest contains no valid audio",
    "多说话人训练集辅助": "Multi-speaker Dataset Helper",
    "失败": "Failed",
    "失败记录": "Failure records",
    "子进程执行失败，返回码：%s": "Child process failed with exit code: %s",
    "实验名不能为空": "Experiment name is required",
    "导出文件格式": "Export file format",
    "已停止": "Stopped",
    "已加载判别器预训练模型：%s": "Loaded discriminator pretrained model: %s",
    "已加载生成器预训练模型：%s": "Loaded generator pretrained model: %s",
    "已启用索引检索": "Index search enabled",
    "已完成": "Completed",
    "已完成阶段": "Completed stages",
    "已恢复判别器检查点": "Restored discriminator checkpoint",
    "已成功": "Succeeded",
    "常见问题解答": "FAQ (Frequently Asked Questions)",
    "常规设置": "General settings",
    "底层模型": "Underlying model",
    "开始音频转换": "Start audio conversion",
    "当前": "Current",
    "当前设备：%s | 推理精度：%s": "Current device: %s | Inference precision: %s",
    "当前阶段": "Current stage",
    "很遗憾您这没有能用的显卡来支持您训练": "Unfortunately, there is no compatible GPU available to support your training.",
    "性别因子/声线粗细": "Gender factor / voice thickness",
    "性能设置": "Performance settings",
    "总训练轮数total_epoch": "Total training epochs (total_epoch):",
    "成功": "Success",
    "执行命令": "Command",
    "批量推理": "Batch Inference",
    "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. ": "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').",
    "拖拽或点击上传待处理音频": "Drag and drop or click to upload audio for processing",
    "指定输出文件夹": "Specify output folder:",
    "推理时间(ms):": "Inference time (ms):",
    "推理耗时：%.2f秒": "Inference time: %.2f seconds",
    "推理音色": "Inferencing voice:",
    "提交训练集清单": "Submit dataset manifest",
    "提取": "Extract",
    "提取音高和处理数据使用的CPU进程数": "Number of CPU processes used for pitch extraction and data processing:",
    "数据切分": "Data slicing",
    "数据切分没有生成16k音频，已停止后续特征提取和训练": "Dataset preprocessing produced no 16 kHz audio. Feature extraction and training have been stopped.",
    "数据切分没有生成有效训练音频，请检查训练集和数据切分日志": "Dataset preprocessing produced no valid training audio. Check the dataset and preprocessing log.",
    "数据切分输出文件不匹配，已停止后续特征提取和训练": "Dataset preprocessing outputs do not match. Feature extraction and training have been stopped.",
    "数据提取开始：start_time=%.6f，请求并行数=%s，实际并行数上限=%s": "Data extraction started: start_time=%.6f, requested concurrency=%s, actual concurrency limit=%s",
    "数据提取结束：end_time=%.6f，总耗时=%.3f秒": "Data extraction finished: end_time=%.6f, total elapsed=%.3f seconds",
    "新增一行": "Add row",
    "无法停止": "Cannot stop",
    "是": "Yes",
    "是否仅保存最新的ckpt文件以节省硬盘空间": "Save only the latest '.ckpt' file to save disk space:",
    "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 final model to the 'weights' folder at each save point:",
    "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": "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training, but caching large datasets will consume a lot of GPU memory and may not provide much speed improvement:",
    "显卡信息": "GPU Information",
    "未使用": "Not used",
    "未使用判别器预训练模型": "Discriminator pretrained model not used",
    "未使用生成器预训练模型": "Generator pretrained model not used",
    "未检测到可用显卡，将使用CPU训练，耗时可能较长": "No supported GPU detected; training on the CPU may take much longer",
    "未运行": "Not running",
    "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>LICENSE</b>.": "This software is open source under the MIT license. The author does not have any control over the software. Users who use the software and distribute the sounds exported by the software are solely responsible. <br>If you do not agree with this clause, you cannot use or reference any codes and files within the software package. See the root directory <b>Agreement-LICENSE.txt</b> for details.",
    "查看": "View",
    "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 supported for small model files extracted from the 'weights' folder)",
    "检索特征占比": "Search feature ratio (controls accent strength, too high has artifacting):",
    "模型信息：%s\n采样率：%s\n是否使用音高引导：%s\n版本：%s": "Model information: %s\nSample rate: %s\nPitch guidance: %s\nVersion: %s",
    "模型推理": "Model Inference",
    "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). This is useful if you want to stop training halfway and manually extract and save a small model file, or if you want to test an intermediate model:",
    "模型是否带音高指导": "Whether the model has pitch guidance:",
    "模型是否带音高指导(唱歌一定要, 语音可以不要)": "Whether the model has pitch guidance (required for singing, optional for speech):",
    "模型是否带音高指导,1是0否": "Whether the model has pitch guidance (1: yes, 0: no):",
    "模型版本型号": "Model architecture version:",
    "模型融合, 可用于测试音色融合": "Model fusion, can be used to test timbre fusion",
    "模型融合失败：两个模型的结构不一致": "Model merge failed: the two model architectures do not match",
    "模型训练": "Model training",
    "模型路径": "Path to Model:",
    "正在保存最终检查点：%s": "Saving final checkpoint: %s",
    "正在保存检查点 %s_e%s：%s": "Saving checkpoint %s_e%s: %s",
    "正在加载RMVPE模型": "Loading RMVPE model",
    "正在加载模型": "Loading model",
    "正在启动": "Starting",
    "正在收尾": "Finalizing",
    "正在预热CUDA Graph": "Warming up CUDA Graph",
    "每张显卡的batch_size": "Batch size per GPU:",
    "没有可用于训练的有效音频，请先完成数据切分和特征提取": "No valid audio is available for training. Complete dataset preprocessing and feature extraction first.",
    "没有有效的多说话人训练集行": "There are no valid multi-speaker dataset rows",
    "淡入淡出长度": "Fade length",
    "清理模型缓存": "Clearing model cache",
    "版本": "Version",
    "特征": "Features",
    "特征提取": "Feature extraction",
    "特征检索库文件路径（选择模型后自动匹配，可手动修改）": "Feature index path (automatically matched after selecting a model; editable)",
    "状态": "Status",
    "独占 WASAPI 设备": "Exclusive WASAPI device",
    "生成器预训练模型不存在，将不使用：assets/pretrained%s/%sG%s.pth": "Generator pretrained model not found; it will not be used: assets/pretrained%s/%sG%s.pth",
    "留空则使用辅助页已提交的清单": "Leave empty to use the manifest submitted from the helper tab",
    "目标采样率": "Target sample rate:",
    "第%s/%s页，共%s行": "Page %s/%s, %s rows",
    "等待中": "Waiting",
    "等待输入": "Waiting for input",
    "算法延迟(ms):": "Algorithmic delays(ms):",
    "索引": "Index",
    "索引文件不存在，将不使用索引继续推理：%s": "Index file does not exist; inference will continue without an index: %s",
    "索引无效：必须使用added_xxxx.index，不能使用trained_xxxx.index": "Invalid index: use added_xxxx.index, not trained_xxxx.index",
    "索引检索失败": "Index search failed",
    "索引检索失败或未启用": "Index search failed or is disabled",
    "索引训练": "Index training",
    "耗时": "Elapsed time",
    "耗时：特征=%.3f秒，索引=%.3f秒，音高=%.3f秒，模型=%.3f秒": "Elapsed time: features=%.3fs, index=%.3fs, pitch=%.3fs, model=%.3fs",
    "融合": "Fusion",
    "要改的模型信息": "Model information to be modified:",
    "要置入的模型信息": "Model information to be placed:",
    "训练": "Train",
    "训练已完成，正在保存最终模型": "Training completed; saving the final model",
    "训练文件列表写入完成": "Training file list written successfully",
    "训练模型": "Train model",
    "训练特征索引": "Train feature index",
    "训练设备规则选择的精度：%s": "Training precision selected by device rules: %s",
    "训练轮次：{} [{:.0f}%]": "Training epoch: {} [{:.0f}%]",
    "训练集子音频文件夹目录路径": "Dataset audio subfolder path",
    "训练集类型": "Dataset type",
    "设备类型": "Device type",
    "说话人ID（0~109）": "Speaker ID (0-109)",
    "说话人名称": "Speaker name",
    "说话人：%s（ID：%s）": "Speaker: %s (ID: %s)",
    "请上传音频文件": "Upload an audio file",
    "请填写输出文件夹路径": "Enter the output folder path",
    "请指定说话人id": "Please specify the speaker/singer ID:",
    "请选择index文件": "Please choose the .index file",
    "请选择pth文件": "Please choose the .pth file",
    "请选择说话人id": "Select Speaker/Singer ID:",
    "转换": "Convert",
    "输入实验名": "Enter the experiment name:",
    "输入实验名，例如：test": "Experiment name, for example: test",
    "输入待处理音频文件夹路径": "Enter the path of the audio folder to be processed:",
    "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 (copy it from the address bar of the file manager):",
    "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": "Adjust the volume envelope scaling. Closer to 0, the more it mimicks the volume of the original vocals. Can help mask noise and make volume sound more natural when set relatively low. Closer to 1 will be more of a consistently loud volume:",
    "输入监听": "Input voice monitor",
    "输入训练文件夹路径": "Enter the path of the training folder:",
    "输入设备": "Input device",
    "输入设备：%s:%s": "Input device: %s:%s",
    "输入降噪": "Input noise reduction",
    "输出信息": "Output information",
    "输出变声": "Output converted voice",
    "输出设备": "Output device",
    "输出设备：%s:%s": "Output device: %s:%s",
    "输出降噪": "Output noise reduction",
    "输出音频(右下角三个点,点了可以下载)": "Export audio (click on the three dots in the lower right corner to download)",
    "运行中": "Running",
    "进度": "Progress",
    "选择.index文件": "Select the .index file",
    "选择.pth文件": "Select the .pth file",
    "选择多说话人音色": "Select multi-speaker voice",
    "选择模型": "Select model",
    "选择索引": "Select index",
    "选择音高提取算法": "Select the pitch extraction algorithm",
    "采样率:": "Sample rate:",
    "采样长度": "Sample length",
    "重复次数": "Repeat count",
    "重载设备列表": "Reload device list",
    "音调设置": "Pitch settings",
    "音频设备": "Audio device",
    "音高全部为0，该音频无意义，跳过：%s": "All pitch values are zero; this audio is unusable and will be skipped: %s",
    "音高算法": "pitch detection algorithm",
    "额外推理时长": "Extra inference time"
}