chore(i18n): sync locale on dev (#35)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

i18n/locale/en_US.json

@@ -1,12 +1,12 @@
 {
+    "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.",
     "### Model extraction\n> Enter the path of the large file model under the 'logs' folder.\n\nThis 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.": "### Model extraction\n> Enter the path of the large file model under the 'logs' folder.\n\nThis 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.",
     "### Model fusion\nCan be used to test timbre fusion.": "### Model fusion\nCan be used to test timbre fusion.",
     "### Modify model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Modify model information\n> Only supported for small model files extracted from the 'weights' folder.",
     "### Step 1. Fill in the experimental configuration.\nExperimental 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.": "### Step 1. Fill in the experimental configuration.\nExperimental 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.",
     "### Step 2. Audio processing. \n#### 1. Slicing.\nAutomatically traverse all files in the training folder that can be decoded into audio and perform slice normalization. Generates 2 wav folders in the experiment directory. Currently, only single-singer/speaker training is supported.": "### Step 2. Audio processing. \n#### 1. Slicing.\nAutomatically traverse all files in the training folder that can be decoded into audio and perform slice normalization. Generates 2 wav folders in the experiment directory. Currently, only single-singer/speaker training is supported.",
     "### Step 3. Start training.\nFill in the training settings and start training the model and index.": "### Step 3. Start training.\nFill in the training settings and start training the model and index.",
     "### View model information\n> Only supported for small model files extracted from the 'weights' folder.": "### View model information\n> Only supported for small model files extracted from the 'weights' folder.",
-    "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度",
     "#### 2. Feature extraction.\nUse CPU to extract pitch (if the model has pitch), use GPU to extract features (select GPU index).": "#### 2. Feature extraction.\nUse CPU to extract pitch (if the model has pitch), use GPU to extract features (select GPU index).",
     "Actually calculated": "Actually calculated",
     "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": "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",
@@ -155,6 +155,5 @@
     "ckpt Processing": "ckpt Processing",
     "index path cannot contain unicode characters": "index path cannot contain unicode characters",
     "pth path cannot contain unicode characters": "pth path cannot contain unicode characters",
-    "step2:Pitch extraction & feature extraction": "step2:Pitch extraction & feature extraction",
-    "模型作者": "模型作者"
+    "step2:Pitch extraction & feature extraction": "step2:Pitch extraction & feature extraction"
 }

i18n/locale/es_ES.json

@@ -1,12 +1,12 @@
 {
+    "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.",
     "### Model extraction\n> Enter the path of the large file model under the 'logs' folder.\n\nThis 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.": "### Extracción de modelo\n> Ingrese la ruta de un archivo de modelo grande en la carpeta 'logs'.\n\nAplicable cuando desea extraer un archivo de modelo pequeño después de entrenar a mitad de camino y no se guardó automáticamente, o cuando desea probar un modelo intermedio.",
     "### Model fusion\nCan be used to test timbre fusion.": "### Model fusion\nCan be used to test timbre fusion.",
     "### Modify model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Modificar la información del modelo\n> Solo admite archivos de modelos pequeños extraídos en la carpeta 'weights'.",
     "### Step 1. Fill in the experimental configuration.\nExperimental 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.": "### Step 1. Fill in the experimental configuration.\nExperimental 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.",
     "### Step 2. Audio processing. \n#### 1. Slicing.\nAutomatically traverse all files in the training folder that can be decoded into audio and perform slice normalization. Generates 2 wav folders in the experiment directory. Currently, only single-singer/speaker training is supported.": "### Paso dos: Procesamiento de audio\n#### 1. Segmentación de audio\nRecorre automáticamente todos los archivos que se pueden decodificar en audio en la carpeta de entrenamiento y realiza la segmentación y normalización, generando 2 carpetas wav en el directorio del experimento; por ahora solo se admite el entrenamiento individual.",
     "### Step 3. Start training.\nFill in the training settings and start training the model and index.": "### Paso tres: Comienza el entrenamiento\nCompleta la configuración de entrenamiento, comienza a entrenar el modelo y el índice.",
     "### View model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Ver información del modelo\n> Solo aplicable a archivos de modelos pequeños extraídos de la carpeta 'weights'.",
-    "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度": "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度",
     "#### 2. Feature extraction.\nUse CPU to extract pitch (if the model has pitch), use GPU to extract features (select GPU index).": "#### 2. Extracción de características\nUtiliza la CPU para extraer el tono (si el modelo tiene tono), utiliza la GPU para extraer características (selecciona el número de tarjeta).",
     "Actually calculated": "Valor realmente calculado",
     "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": "Proporción de fusión para reemplazar el sobre de volumen de entrada con el sobre de volumen de salida, cuanto más cerca de 1, más se utiliza el sobre de salida",
@@ -155,6 +155,5 @@
     "ckpt Processing": "Procesamiento de recibos",
     "index path cannot contain unicode characters": "La ruta del archivo .index no debe contener caracteres chinos.",
     "pth path cannot contain unicode characters": "La ruta del archivo .pth no debe contener caracteres chinos.",
-    "step2:Pitch extraction & feature extraction": "Paso 2: Extracción del tono y extracción de características",
-    "模型作者": "模型作者"
+    "step2:Pitch extraction & feature extraction": "Paso 2: Extracción del tono y extracción de características"
 }

i18n/locale/fr_FR.json

@@ -1,12 +1,12 @@
 {
+    "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.",
     "### Model extraction\n> Enter the path of the large file model under the 'logs' folder.\n\nThis 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.": "### Extraction du modèle\n> Saisissez le chemin d'accès au modèle du grand fichier dans le dossier \"logs\".\n\nCette fonction est utile si vous souhaitez arrêter l'entrainement à mi-chemin et extraire et enregistrer manuellement un petit fichier de modèle, ou si vous souhaitez tester un modèle intermédiaire.",
     "### Model fusion\nCan be used to test timbre fusion.": "### Model fusion\nCan be used to test timbre fusion.",
     "### Modify model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Modifier les informations du modèle\n> Uniquement pris en charge pour les petits fichiers de modèle extraits du dossier 'weights'.",
     "### Step 1. Fill in the experimental configuration.\nExperimental 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.": "### Step 1. Fill in the experimental configuration.\nExperimental 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.",
     "### Step 2. Audio processing. \n#### 1. Slicing.\nAutomatically traverse all files in the training folder that can be decoded into audio and perform slice normalization. Generates 2 wav folders in the experiment directory. Currently, only single-singer/speaker training is supported.": "### Deuxième étape : Traitement audio\n#### 1. Découpage de l'audio\nParcourez automatiquement tous les fichiers qui peuvent être décodés en audio dans le dossier d'entraînement et effectuez le découpage et la normalisation. Deux dossiers wav sont générés dans le répertoire de l'expérience. Pour le moment, seul l'entraînement individuel est pris en charge.",
     "### Step 3. Start training.\nFill in the training settings and start training the model and index.": "### Troisième étape : Commencer l'entraînement\nRemplissez les paramètres d'entraînement, commencez à entraîner le modèle et l'index.",
     "### View model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Afficher les informations sur le modèle\n> Uniquement pour les petits fichiers de modèle extraits du dossier 'weights'.",
-    "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度": "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度",
     "#### 2. Feature extraction.\nUse CPU to extract pitch (if the model has pitch), use GPU to extract features (select GPU index).": "#### 2. Extraction des caractéristiques\nUtilisez le CPU pour extraire la hauteur tonale (si le modèle a une hauteur tonale), utilisez le GPU pour extraire les caractéristiques (sélectionnez le numéro de carte).",
     "Actually calculated": "Effectivement calculé",
     "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": "Ajustez l'échelle de l'enveloppe de volume. Plus il est proche de 0, plus il imite le volume des voix originales. Cela peut aider à masquer les bruits et à rendre le volume plus naturel lorsqu'il est réglé relativement bas. Plus le volume est proche de 1, plus le volume sera fort et constant :",
@@ -155,6 +155,5 @@
     "ckpt Processing": "Traitement des fichiers .ckpt",
     "index path cannot contain unicode characters": "Le chemin du fichier d'index ne doit pas contenir de caractères chinois.",
     "pth path cannot contain unicode characters": "Le chemin du fichier .pth ne doit pas contenir de caractères chinois.",
-    "step2:Pitch extraction & feature extraction": "Étape 2 : Extraction de la hauteur et extraction des caractéristiques en cours.",
-    "模型作者": "模型作者"
+    "step2:Pitch extraction & feature extraction": "Étape 2 : Extraction de la hauteur et extraction des caractéristiques en cours."
 }

i18n/locale/it_IT.json

@@ -1,12 +1,12 @@
 {
+    "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Model comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.",
     "### Model extraction\n> Enter the path of the large file model under the 'logs' folder.\n\nThis 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.": "### Estrazione del modello\n> Inserire il percorso del modello di file di grandi dimensioni nella cartella \"logs\".",
     "### Model fusion\nCan be used to test timbre fusion.": "### Model fusion\nCan be used to test timbre fusion.",
     "### Modify model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Modifica le informazioni sul modello\n> Supportato solo per i file di modello di piccole dimensioni estratti dalla cartella 'weights'.",
     "### Step 1. Fill in the experimental configuration.\nExperimental 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.": "### Step 1. Fill in the experimental configuration.\nExperimental 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.",
     "### Step 2. Audio processing. \n#### 1. Slicing.\nAutomatically traverse all files in the training folder that can be decoded into audio and perform slice normalization. Generates 2 wav folders in the experiment directory. Currently, only single-singer/speaker training is supported.": "### 第二步 音频处理\n#### 1. 音频切片\n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.",
     "### Step 3. Start training.\nFill in the training settings and start training the model and index.": "### 第三步 开始训练\n填写训练设置, 开始训练模型和索引.",
     "### View model information\n> Only supported for small model files extracted from the 'weights' folder.": "### Visualizza le informazioni sul modello\n> Supportato solo per file di modello piccoli estratti dalla cartella 'weights'.",
-    "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度": "### 模型比较\n> 模型ID(长)请于下方`查看模型信息`中获得\n\n可用于比较两模型推理相似度",
     "#### 2. Feature extraction.\nUse CPU to extract pitch (if the model has pitch), use GPU to extract features (select GPU index).": "#### 2. 特征提取\n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).",
     "Actually calculated": "实际计算",
     "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": "Regola il ridimensionamento dell'inviluppo del volume. ",
@@ -155,6 +155,5 @@
     "ckpt Processing": "Elaborazione ckpt",
     "index path cannot contain unicode characters": "index文件路径不可包含中文",
     "pth path cannot contain unicode characters": "pth è un'app per il futuro",
-    "step2:Pitch extraction & feature extraction": "step2:正在提取音高&正在提取特征",
-    "模型作者": "模型作者"
+    "step2:Pitch extraction & feature extraction": "step2:正在提取音高&正在提取特征"
 }