Fix(l10n): Update translations from Transifex

Signed-off-by: Nextcloud bot <[email protected]>

l10n/zh_HK.js

@@ -3,14 +3,14 @@ OC.L10N.register(
     {
     "Recognize" : "識別",
     "Smart media tagging and face recognition with on-premises machine learning models" : "使用本地機器學習模型進行智能媒體標記和人臉識別",
-    "Smart media tagging and face recognition with on-premises machine learning models.\nThis app goes through your media collection and adds fitting tags, automatically categorizing your photos and music.\n\n* 📷 👪 Recognizes faces from contact photos\n* 📷 🏔 Recognizes animals, landscapes, food, vehicles, buildings and other objects\n* 📷 🗼 Recognizes landmarks and monuments\n* 👂 🎵 Recognizes music genres\n* 🎥 🤸 Recognizes human actions on video\n\n⚡ Tagging works via Nextcloud's Collaborative Tags\n  * 👂 listen to your tagged music with the audioplayer app\n  * 📷 view your tagged photos and videos with the photos app\n\nModel sizes:\n\n * Object recognition: 1GB\n * Landmark recognition: 300MB\n * Video action recognition: 50MB\n * Music genre recognition: 50MB\n\n## Ethical AI Rating\n### Rating for Photo object detection: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Photo face recognition: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Video action recognition: 🟢\n\nPositive:\n* the software for training and inferencing of this model is open source\n* the trained model is freely available, and thus can be ran on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n## Ethical AI Rating\n### Rating Music genre recognition: 🟡\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n\nNegative:\n* the training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\nLearn more about the Nextcloud Ethical AI Rating [in our blog](https://nextcloud.com/blog/nextcloud-ethical-ai-rating/).\n\nAfter installation, you can enable tagging in the admin settings.\n\nRequirements:\n- php 7.4 and above\n- App \"collaborative tags\" enabled\n- For native speed:\n  - Processor: x86 64-bit (with support for AVX instructions)\n  - System with glibc (usually the norm on Linux; FreeBSD, Alpine linux and thus also the official Nextcloud Docker container and Nextcloud AIO are *not* such systems)\n- For sub-native speed (using WASM mode)\n  - Processor: x86 64-bit, arm64, armv7l (no AVX needed)\n  - System with glibc or musl (incl. Alpine linux and thus also the official Nextcloud Docker container and also Nextcloud AIO)\n- ~4GB of free RAM (if you're cutting it close, make sure you have some swap available)\n- This app is currently incompatible with the *Suspicious Login* app due to a dependency conflict (ie. you can only have one of the two installed)\n\nThe app does not send any sensitive data to cloud providers or similar services. All processing is done on your Nextcloud machine, using Tensorflow.js running in Node.js." : "使用本地機器學習模型進行智能媒體標記和人臉識別\n\n此應用程式會遍歷您收藏的媒體並對其添加合適的標籤，自動對您的照片和音樂進行分類。\n\n* 📷 👪 從聯絡人照片中識別面孔\n* 📷 🏔 識別動物、風景、食物、車輛、建築物和其他物體\n* 📷 🗼 識別地標和紀念碑\n* 👂 🎵 識別音樂流派\n* ⚡ 通過 Nextcloud 的協作標籤進行標記，允許您的任何應用程序進行訪問\n* 👂 使用音頻播放器應用程序聆聽您標記的音樂\n* 📷 使用照片應用程式查看您標記的照片\n\n## 道德人工智能評級\n### 照片對象檢測評級：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n### 照片人臉識別評分：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n### 視頻動作識別評級：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n## 道德人工智能評級\n### 評級音樂流派識別：🟡\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n\n消極的：\n* 訓練數據不是免費提供的，這限制了外部各方檢查和糾正偏差或優化模型性能和二氧化碳使用的能力。\n\n了解有關 Nextcloud 道德 AI 評級的更多信息 [在我們的博客中](https://nextcloud.com/blog/nextcloud-ethical-ai- rating/)。\n\n安裝後，您可以在管理設置中啟用標記。\n\n要求：\n- PHP 7.4 及以上版本\n- 啟用應用程序“協作標籤”\n- 對於本機速度：\n- 處理器：x86 64 位（支持 AVX 指令）\n- 具有 glibc 的系統（通常是 Linux 上的標準；FreeBSD、Alpine linux 以及官方 Nextcloud Docker 容器和 Nextcloud AIO *不是*此類系統）\n- 低於本機速度（使用 WASM 模式）\n- 處理器：x86 64 位、arm64、armv7l（無需 AVX）\n- 具有 glibc 或 musl 的系統（包括 Alpine linux，因此也是官方 Nextcloud Docker 容器和 Nextcloud AIO）\n- ~4GB 可用 RAM（如果您要削減它，請確保有一些可用的交換空間）\n- 由於依賴性衝突，此應用程序當前與*可疑登錄*應用程序不兼容（即您只能安裝兩者之一）\n\n該應用程式不會向雲提供商或類似服務發送任何敏感數據。 所有處理都是在您的 Nextcloud 計算機上使用在 Node.js 中運行的 Tensorflow.js 完成的。",
+    "Smart media tagging and face recognition with on-premises machine learning models.\nThis app goes through your media collection and adds fitting tags, automatically categorizing your photos and music.\n\n* 📷 👪 Recognizes faces from contact photos\n* 📷 🏔 Recognizes animals, landscapes, food, vehicles, buildings and other objects\n* 📷 🗼 Recognizes landmarks and monuments\n* 👂 🎵 Recognizes music genres\n* 🎥 🤸 Recognizes human actions on video\n\n⚡ Tagging works via Nextcloud's Collaborative Tags\n  * 👂 listen to your tagged music with the audioplayer app\n  * 📷 view your tagged photos and videos with the photos app\n\nModel sizes:\n\n * Object recognition: 1GB\n * Landmark recognition: 300MB\n * Video action recognition: 50MB\n * Music genre recognition: 50MB\n\n## Ethical AI Rating\n### Rating for Photo object detection: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Photo face recognition: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Video action recognition: 🟢\n\nPositive:\n* the software for training and inferencing of this model is open source\n* the trained model is freely available, and thus can be ran on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n## Ethical AI Rating\n### Rating Music genre recognition: 🟡\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n\nNegative:\n* the training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\nLearn more about the Nextcloud Ethical AI Rating [in our blog](https://nextcloud.com/blog/nextcloud-ethical-ai-rating/).\n\nAfter installation, you can enable tagging in the admin settings.\n\nRequirements:\n- php 7.4 and above\n- App \"collaborative tags\" enabled\n- For native speed:\n  - Processor: x86 64-bit (with support for AVX instructions)\n  - System with glibc (usually the norm on Linux; FreeBSD, Alpine linux and thus also the official Nextcloud Docker container and Nextcloud AIO are *not* such systems)\n- For sub-native speed (using WASM mode)\n  - Processor: x86 64-bit, arm64, armv7l (no AVX needed)\n  - System with glibc or musl (incl. Alpine linux and thus also the official Nextcloud Docker container and also Nextcloud AIO)\n- ~4GB of free RAM (if you're cutting it close, make sure you have some swap available)\n- This app is currently incompatible with the *Suspicious Login* app due to a dependency conflict (ie. you can only have one of the two installed)\n\nThe app does not send any sensitive data to cloud providers or similar services. All processing is done on your Nextcloud machine, using Tensorflow.js running in Node.js." : "使用本地機器學習模型進行智能媒體標記和人臉識別\n\n此應用程式會遍歷您收藏的媒體並對其添加合適的標籤，自動對您的照片和音樂進行分類。\n\n* 📷 👪 從聯絡人照片中識別面孔\n* 📷 🏔 識別動物、風景、食物、車輛、建築物和其他物體\n* 📷 🗼 識別地標和紀念碑\n* 👂 🎵 識別音樂流派\n* ⚡ 通過 Nextcloud 的協作標籤進行標記，允許您的任何應用程序進行訪問\n* 👂 使用音頻播放器應用程序聆聽您標記的音樂\n* 📷 使用照片應用程式查看您標記的照片\n\n## 道德人工智能評級\n### 照片對象檢測評級：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n### 照片人臉識別評分：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n### 視頻動作識別評級：🟢\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n* 訓練數據是免費提供的，可以檢查或糾正偏差或優化性能和二氧化碳的使用。\n\n## 道德人工智能評級\n### 評級音樂流派識別：🟡\n\n積極的：\n* 該模型的訓練和推理軟件是開源的\n* 經過訓練的模型是免費提供的，因此可以在本地運行\n\n消極的：\n* 訓練數據不是免費提供的，這限制了外部各方檢查和糾正偏差或優化模型性能和二氧化碳使用的能力。\n\n了解有關 Nextcloud 道德 AI 評級的更多信息 [在我們的博客中](https://nextcloud.com/blog/nextcloud-ethical-ai- rating/)。\n\n安裝後，您可以在管理設置中啟用標記。\n\n要求：\n- PHP 7.4 及以上版本\n- 啟用應用程序“協作標籤”\n- 對於本機速度：\n- 處理器：x86 64 位（支持 AVX 指令）\n- 具有 glibc 的系統（通常是 Linux 上的標準；FreeBSD、Alpine linux 以及官方 Nextcloud Docker 容器和 Nextcloud AIO *不是*此類系統）\n- 低於本機速度（使用 WASM 模式）\n- 處理器：x86 64 位、arm64、armv7l（無需 AVX）\n- 具有 glibc 或 musl 的系統（包括 Alpine linux，因此也是官方 Nextcloud Docker 容器和 Nextcloud AIO）\n- ~4GB 可用 RAM（如果您要削減它，請確保有一些可用的交換空間）\n- 由於依賴性衝突，此應用程序目前與*可疑登錄*應用程序不兼容（即您只能安裝兩者之一）\n\n該應用程式不會向雲提供商或類似服務發送任何敏感數據。 所有處理都是在您的 Nextcloud 計算機上使用在 Node.js 中運行的 Tensorflow.js 完成的。",
     "Status" : "狀態",
     "The machine learning models have been downloaded successfully." : "機器學習模型已成功下載。",
     "The machine learning models still need to be downloaded." : "機器學習模型仍然需要下載。",
     "Could not execute the Node.js binary. You may need to set the path to a working binary manually." : "Could not execute the Node.js binary. You may need to set the path to a working binary manually.",
     "Background Jobs are not executed via cron. Recognize requires background jobs to be executed via cron." : "後台作業不通過 cron 執行。Recognize 需要通過 cron 執行後台作業。",
     "The app is installed and will automatically classify files in background processes." : "該應用程式已安裝，並將自動對後台進程中的檔案進行分類。",
-    "None of the tagging options below are currently selected. The app will currently do nothing." : "當前未選擇以下任何標記選項。該應用程式目前不會執行任何操作。",
+    "None of the tagging options below are currently selected. The app will currently do nothing." : "目前未選擇以下任何標記選項。該應用程式目前不會執行任何操作。",
     "Face recognition" : "人臉識別",
     "Face recognition is working. " : "人臉識別中。",
     "An error occurred during face recognition, please check the Nextcloud logs." : "人臉識別出錯，請查看 Nextcloud 記錄。",
@@ -89,8 +89,8 @@ OC.L10N.register(
     "Libtensorflow was loaded successfully into Node.js." : "Libtensorflow WASM 已成功加載到 Node.js 中。",
     "Could not load Tensorflow WASM in Node.js. Something is wrong with your setup." : "無法在 Node.js 中加載 TensorFlow WASM。您的設置有問題。",
     "Tensorflow WASM was loaded successfully into Node.js." : "TensorFlow WASM 已成功加載到 Node.js 中。",
-    "If the shipped Node.js binary doesn't work on your system for some reason you can set the path to a custom node.js binary. Currently supported is Node v20.9 and newer v20 releases." : "如果隨附的 Node.js 二進製文件由於某種原因無法在您的系統上運行，您可以將路徑設置為自定義 node.js 二進製文件。當前支持的是 Node v20.9 和更新的 v20 版本。",
-    "For Nextcloud Snap users, you need to adjust this path to point to the snap's \"current\" directory as the pre-configured path will change with each update. For example, set it to \"/var/snap/nextcloud/current/nextcloud/extra-apps/recognize/bin/node\" instead of \"/var/snap/nextcloud/9337974/nextcloud/extra-apps/recognize/bin/node\"" : "對於 Nextcloud Snap 用戶，您需要調整此路徑以指向快照的“當前”目錄，因為預配置的路徑會隨著每次更新而更改。例如，將其設置為“/var/snap/nextcloud/current/nextcloud/extra-apps/recognize/bin/node”而不是“/var/snap/nextcloud/9337974/nextcloud/extra-apps/recognize/bin/node”",
+    "If the shipped Node.js binary doesn't work on your system for some reason you can set the path to a custom node.js binary. Currently supported is Node v20.9 and newer v20 releases." : "如果隨附的 Node.js 二進製文件由於某種原因無法在您的系統上運行，您可以將路徑設置為自定義 node.js 二進製文件。目前支持的是 Node v20.9 和更新的 v20 版本。",
+    "For Nextcloud Snap users, you need to adjust this path to point to the snap's \"current\" directory as the pre-configured path will change with each update. For example, set it to \"/var/snap/nextcloud/current/nextcloud/extra-apps/recognize/bin/node\" instead of \"/var/snap/nextcloud/9337974/nextcloud/extra-apps/recognize/bin/node\"" : "對於 Nextcloud Snap 用戶，您需要調整此路徑以指向快照的“目前”目錄，因為預配置的路徑會隨著每次更新而更改。例如，將其設置為“/var/snap/nextcloud/current/nextcloud/extra-apps/recognize/bin/node”而不是“/var/snap/nextcloud/9337974/nextcloud/extra-apps/recognize/bin/node”",
     "Classifier process priority" : "分類器進程優先級",
     "Checking Nice binary" : "檢查 Nice 二進製檔案",
     "Could not find the Nice binary. You may need to set the path to a working binary manually." : "找不到 Nice 二進製檔案。您可能需要手動設置正常運行二進製檔案的路徑。",