Merge pull request #395 from MicrosoftDocs/main

Sync main to release-llama-winter-2024

Author: Albertyang0

articles/ai-services/.openpublishing.redirection.ai-services.json

@@ -315,6 +315,11 @@
       "redirect_url": "/azure/ai-services/computer-vision/sdk/install-sdk",
       "redirect_document_id": true
     },
+    {
+      "source_path_from_root": "/articles/ai-services/computer-vision/how-to/migrate-from-custom-vision.md",
+      "redirect_url": "/azure/ai-services/computer-vision/how-to/model-customization",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/articles/ai-services/document-intelligence/concept-document-intelligence-studio.md",
       "redirect_url": "/azure/ai-services/document-intelligence/studio-overview",
@@ -395,6 +400,11 @@
       "redirect_url": "/azure/ai-services/speech-service/quickstarts/setup-platform",
       "redirect_document_id": false
     },
+    {
+      "source_path_from_root": "/articles/ai-services/speech-service/devices-sdk-release-notes.md",
+      "redirect_url": "/azure/ai-services/speech-service/release-notes",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/articles/ai-services/anomaly-detector/how-to/postman.md",
       "redirect_url": "/azure/ai-services/anomaly-detector/overview",

articles/ai-services/computer-vision/concept-model-customization.md

@@ -14,6 +14,8 @@ ms.author: pafarley
 
 # Model customization (version 4.0 preview)
 
+[!INCLUDE [model-customization-deprecation](includes/model-customization-deprecation.md)]
+
 Model customization lets you train a specialized Image Analysis model for your own use case. Custom models can do either image classification (tags apply to the whole image) or object detection (tags apply to specific areas of the image). Once your custom model is created and trained, it belongs to your Vision resource, and you can call it using the [Analyze Image API](./how-to/call-analyze-image-40.md).
 
 Implement model customization quickly and easily by following a quickstart:

articles/ai-services/computer-vision/concept-object-detection-40.md

@@ -23,8 +23,6 @@ Try out the capabilities of object detection quickly and easily in your browser
 > [!div class="nextstepaction"]
 > [Try Vision Studio](https://portal.vision.cognitive.azure.com/)
 
-> [!TIP]
-> You can use the Object detection feature through the [Azure OpenAI](/azure/ai-services/openai/overview) service. The **GPT-4 Turbo with Vision** model lets you chat with an AI assistant that can analyze the images you share, and the Vision Enhancement option uses Image Analysis to provide the AI assistance with more details (readable text and object locations) about the image. For more information, see the [GPT-4 Turbo with Vision quickstart](/azure/ai-services/openai/gpt-v-quickstart).
 
 ## Object detection example
 

articles/ai-services/computer-vision/concept-ocr.md

@@ -23,8 +23,6 @@ OCR is a machine-learning-based technique for extracting text from in-the-wild a
 
 The new Azure AI Vision Image Analysis 4.0 REST API offers the ability to extract printed or handwritten text from images in a unified performance-enhanced synchronous API that makes it easy to get all image insights including OCR results in a single API operation. The Read OCR engine is built on top of multiple deep learning models supported by universal script-based models for [global language support](./language-support.md).
 
-> [!TIP]
-> You can also use the OCR feature in conjunction with the [Azure OpenAI](/azure/ai-services/openai/overview) service. The **GPT-4 Turbo with Vision** model lets you chat with an AI assistant that can analyze the images you share, and the Vision Enhancement option uses Image Analysis to give the AI assistant more details (readable text and object locations) about the image. For more information, see the [GPT-4 Turbo with Vision quickstart](/azure/ai-services/openai/gpt-v-quickstart).
 
 ## Text extraction example
 

articles/ai-services/computer-vision/concept-shelf-analysis.md

@@ -15,6 +15,8 @@ ms.custom: build-2023, build-2023-dataai
 
 # Product Recognition (version 4.0 preview)
 
+[!INCLUDE [model-customization-deprecation](includes/model-customization-deprecation.md)]
+
 The Product Recognition APIs let you analyze photos of shelves in a retail store. You can detect the presence of products and get their bounding box coordinates. Use it in combination with model customization to train a model to identify your specific products. You can also compare Product Recognition results to your store's planogram document.
 
 Try out the capabilities of Product Recognition quickly and easily in your browser using Vision Studio.

articles/ai-services/computer-vision/how-to/coco-verification.md

@@ -16,6 +16,8 @@ ms.author: pafarley
 
 <!-- nbstart https://raw.githubusercontent.com/Azure-Samples/cognitive-service-vision-model-customization-python-samples/main/docs/check_coco_annotation.ipynb -->
 
+[!INCLUDE [model-customization-deprecation](../includes/model-customization-deprecation.md)]
+
 > [!TIP]
 > This article is based on the Jupyter notebook _check_coco_annotation.ipynb_. **[Open in GitHub](https://github.com/Azure-Samples/cognitive-service-vision-model-customization-python-samples/blob/main/docs/check_coco_annotation.ipynb)**.