chore(i18n): fix lost locale entries from other languages (except zh_*) (#39)

Author: 413x1nkp

i18n/locale/es_ES.json

@@ -1,9 +1,9 @@
 {
-    "### 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 comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Comparación de modelos\n> Obtén el ID del modelo (largo) en la sección de `Ver información del modelo` a continuación\n\nSe puede utilizar para comparar la similitud de la inferencia de dos modelos.",
     "### 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.",
+    "### Model fusion\nCan be used to test timbre fusion.": "### Fusión de modelos\nSe puede utilizar para fusionar diferentes voces.",
     "### 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 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.": "### Paso 1. Complete la configuración del experimento.\nLos datos del experimento se almacenan en el directorio 'logs', con cada experimento en una carpeta separada. La ruta del nombre del experimento debe ingresarse manualmente y debe contener la configuración del experimento, los registros y los archivos del modelo entrenado.",
     "### 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'.",
@@ -50,7 +50,7 @@
     "Hidden": "Oculto",
     "ID of model A (long)": "ID del modelo A (largo)",
     "ID of model B (long)": "ID del modelo B (largo)",
-    "ID(long)": "ID(long)",
+    "ID(long)": "ID (largo)",
     "ID(short)": "ID (corto)",
     "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Si es >=3, entonces use el resultado del reconocimiento de tono de 'harvest' con filtro de mediana, el valor es el radio del filtro, su uso puede debilitar el sonido sordo",
     "Inference time (ms)": "Inferir tiempo (ms)",

i18n/locale/fr_FR.json

@@ -1,9 +1,9 @@
 {
-    "### 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 comparison\n> You can get model ID (long) from `View model information` below.\n\nCalculate a similarity between two models.": "### Comparaison des modèles\n> Pour obtenir l'ID du modèle (long), veuillez consulter la section `Voir les informations du modèle` ci-dessous.\n\nPeut être utilisé pour comparer la similarité des inférences entre deux modèles.",
     "### 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 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.": "### Étape 1. Remplissez la configuration expérimentale.\nLes données expérimentales sont stockées dans le dossier 'logs', avec chaque expérience ayant un dossier distinct. Entrez manuellement le chemin du nom de l'expérience, qui contient la configuration expérimentale, les journaux et les fichiers de modèle entraînés.",
     "### 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'.",
@@ -50,7 +50,7 @@
     "Hidden": "Caché",
     "ID of model A (long)": "ID du modèle A (long)",
     "ID of model B (long)": "ID du modèle B (long)",
-    "ID(long)": "ID(long)",
+    "ID(long)": "ID (long)",
     "ID(short)": "ID (court)",
     "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Si >=3 : appliquer un filtrage médian aux résultats de la reconnaissance de la hauteur de récolte. La valeur représente le rayon du filtre et peut réduire la respiration.",
     "Inference time (ms)": "Temps d'inférence (ms)",