Merge pull request #1747 from MicrosoftDocs/main

Taojunshen · web-flow · commit 054ac6301b97 · 2024-11-28T01:59:04.000+08:00
11/27/2024 AM Publish
diff --git a/articles/ai-services/.openpublishing.redirection.ai-services.json b/articles/ai-services/.openpublishing.redirection.ai-services.json
@@ -775,6 +775,11 @@
       "redirect_url": "/azure/ai-services/speech-service/video-translation-get-started",
       "redirect_document_id": true
     },
+    {
+      "source_path_from_root": "/articles/ai-services/speech-service/custom-speech-ai-studio.md",
+      "redirect_url": "/azure/ai-services/speech-service/custom-speech-ai-foundry-portal",
+      "redirect_document_id": true
+    },
     {
       "source_path_from_root": "/articles/ai-services/qnamaker/how-to/migrate-to-openai.md",
       "redirect_url": "/azure/ai-services/qnamaker/overview/overview",
diff --git a/articles/ai-services/document-intelligence/studio-overview.md b/articles/ai-services/document-intelligence/studio-overview.md
@@ -27,7 +27,7 @@ The studio is an online tool to visually explore, understand, train, and integra
 * Train custom extraction models to extract fields from documents.
 * Get sample code for the language specific `SDKs` to integrate into your applications.
 
-Currently, we're undergoing the migration of features from the [Document Intelligence Studio](https://documentintelligence.ai.azure.com/studio) to the new [AI Foundry](https://ai.azure.com/explore/aiservices/vision). There are some differences in the offerings for the two studios, which determine the correct studio for your use case.
+Currently, we're undergoing the migration of features from the [Document Intelligence Studio](https://documentintelligence.ai.azure.com/studio) to the new [AI Foundry portal](https://ai.azure.com/explore/aiservices/vision). There are some differences in the offerings for the two studios, which determine the correct studio for your use case.
 
 ## Choosing the correct studio experience
 
@@ -37,7 +37,7 @@ There are currently two studios, the [Azure AI Foundry](https://ai.azure.com/exp
 
 Document Intelligence Studio is the legacy experience that contains all features released on or before July 2024. For any of the v2.1, v3.0, v3.1 features, continue to use the Document Intelligence Studio. Studios provide a visual experience for labeling, training, and validating custom models. For custom document field extraction models, use the Document Intelligence Studio for template and neural models. Custom classification models can only be trained and used on Document Intelligence Studio. Use Document Intelligence Studio if you want to try out GA versions of the models from version 2.1, v3.0 and v3.1.
 
-### When to use [AI Foundry](https://ai.azure.com/explore/aiservices/vision)
+### When to use [AI Foundry portal](https://ai.azure.com/explore/aiservices/vision)
 
 Start with the new Azure AI Foundry and try any of the prebuilt document models from `2024-02-29-preview` version including general extraction models like Read or Layout. If you want to build and test a new [Document Field Extraction](https://ai.azure.com/explore/aiservices/vision/document/extraction) model, try our generative AI model, only available in the new AI Foundry.
 
@@ -210,5 +210,5 @@ Learn how to [connect your AI services hub](../../ai-studio/ai-services/how-to/c
 ## Next steps
 
 * Visit [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio).
-* Visit [AI Foundry](https://ai.azure.com/explore/aiservices/vision).
+* Visit [AI Foundry portal](https://ai.azure.com/explore/aiservices/vision).
 * Get started with [Document Intelligence Studio quickstart](quickstarts/try-document-intelligence-studio.md).
diff --git a/articles/ai-services/openai/assistants-quickstart.md b/articles/ai-services/openai/assistants-quickstart.md
@@ -18,9 +18,9 @@ recommendations: false
 
 Azure OpenAI Assistants (Preview) allows you to create AI assistants tailored to your needs through custom instructions and augmented by advanced tools like code interpreter, and custom functions.
 
-::: zone pivot="programming-language-ai-studio"
+::: zone pivot="ai-foundry-portal"
 
-[!INCLUDE [AI Foundry](includes/assistants-ai-studio.md)]
+[!INCLUDE [AI Foundry portal](includes/assistants-ai-studio.md)]
 
 ::: zone-end
 
diff --git a/articles/ai-services/openai/gpt-v-quickstart.md b/articles/ai-services/openai/gpt-v-quickstart.md
@@ -22,9 +22,9 @@ Get started using GPT-4 Turbo with images with the Azure OpenAI Service.
 >
 > The latest vision-capable models are `gpt-4o` and `gpt-4o mini`. These are in public preview. The latest available GA model is `gpt-4` version `turbo-2024-04-09`.
 
-::: zone pivot="programming-language-studio"
+::: zone pivot="ai-foundry-portal"
 
-[!INCLUDE [Studio quickstart](includes/gpt-v-studio.md)]
+[!INCLUDE [AI Foundry portal quickstart](includes/gpt-v-studio.md)]
 
 ::: zone-end
 
diff --git a/articles/ai-services/openai/how-to/batch.md b/articles/ai-services/openai/how-to/batch.md
@@ -89,9 +89,9 @@ In the AI Foundry portal the deployment type will appear as `Global-Batch`.
 > [!TIP]
 > We recommend enabling **dynamic quota** for all global batch model deployments to help avoid job failures due to insufficient enqueued token quota. Dynamic quota allows your deployment to opportunistically take advantage of more quota when extra capacity is available. When dynamic quota is set to off, your deployment will only be able to process requests up to the enqueued token limit that was defined when you created the deployment.
 
-::: zone pivot="programming-language-ai-studio"
+::: zone pivot="ai-foundry-portal"
 
-[!INCLUDE [Studio](../includes/batch/batch-studio.md)]
+[!INCLUDE [AI Foundry portal](../includes/batch/batch-studio.md)]
 
 ::: zone-end
 
diff --git a/articles/ai-services/openai/how-to/fine-tuning.md b/articles/ai-services/openai/how-to/fine-tuning.md
@@ -10,7 +10,7 @@ ms.topic: how-to
 ms.date: 11/11/2024
 author: mrbullwinkle
 ms.author: mbullwin
-zone_pivot_groups: openai-fine-tuning-newest
+zone_pivot_groups: openai-fine-tuning
 ---
 
 # Customize a model with fine-tuning
diff --git a/articles/ai-services/openai/how-to/weights-and-biases-integration.md b/articles/ai-services/openai/how-to/weights-and-biases-integration.md
@@ -87,7 +87,7 @@ Give your Azure OpenAI resource the **Key Vault Secrets Officer** role.
 
 ## Link Weights & Biases with Azure OpenAI
 
-1. Navigate to [AI Foundry](https://ai.azure.com) and select your Azure OpenAI fine-tuning resource.
+1. Navigate to [AI Foundry portal](https://ai.azure.com) and select your Azure OpenAI fine-tuning resource.
 
     :::image type="content" source="../media/how-to/weights-and-biases/manage-integrations.png" alt-text="Screenshot of the manage integrations button." lightbox="../media/how-to/weights-and-biases/manage-integrations.png":::
 
diff --git a/articles/ai-services/openai/includes/assistants-studio.md b/articles/ai-services/openai/includes/assistants-studio.md
@@ -41,7 +41,7 @@ Use the **Assistant setup** pane to create a new AI assistant or to select an ex
 | **Deployment** | This is where you set which model deployment to use with your assistant. |
 | **Functions**| Create custom function definitions for the models to formulate API calls and structure data outputs based on your specifications |
 | **Code interpreter** | Code interpreter provides access to a sandboxed Python environment that can be used to allow the model to test and execute code. |
-| **Files** | You can upload up to 20 files, with a max file size of 512 MB to use with tools. You can upload up to 10,000 files using [AI Foundry](../assistants-quickstart.md?pivots=programming-language-ai-studio). |
+| **Files** | You can upload up to 20 files, with a max file size of 512 MB to use with tools. You can upload up to 10,000 files using [AI Foundry portal](../assistants-quickstart.md?pivots=ai-foundry-portal). |
 
 ### Tools
 
diff --git a/articles/ai-services/openai/includes/batch/batch-studio.md b/articles/ai-services/openai/includes/batch/batch-studio.md
@@ -70,7 +70,7 @@ For this article, we'll create a file named `test.jsonl` and will copy the conte
 
 Once your input file is prepared, you first need to upload the file to then be able to kick off a batch job. File upload can be done both programmatically or via the Studio.
 
-1. Sign in to [AI Foundry](https://ai.azure.com).
+1. Sign in to [AI Foundry portal](https://ai.azure.com).
 2. Select the Azure OpenAI resource where you have a global batch model deployment available.
 3. Select **Batch jobs** > **+Create batch jobs**.
 
diff --git a/articles/ai-services/openai/includes/fine-tuning-python.md b/articles/ai-services/openai/includes/fine-tuning-python.md
@@ -390,7 +390,7 @@ When the fine-tuning job succeeds, the value of the `fine_tuned_model` variable
 
 [!INCLUDE [Fine-tuning deletion](fine-tune.md)]
 
-You can also use [Azure AI Foundry](/azure/ai-services/openai/how-to/fine-tuning?tabs=turbo%2Cpython-new&pivots=programming-language-ai-studio#deploy-a-fine-tuned-model) or the [Azure CLI](#deploy-a-model-with-azure-cli) to deploy your customized model.
+You can also use [Azure AI Foundry](/azure/ai-services/openai/how-to/fine-tuning?tabs=turbo%2Cpython-new&pivots=ai-foundry-portal#deploy-a-fine-tuned-model) or the [Azure CLI](#deploy-a-model-with-azure-cli) to deploy your customized model.
 
 > [!NOTE]
 > Only one deployment is permitted for a customized model. An error occurs if you select an already-deployed customized model.
@@ -656,14 +656,14 @@ When you're done with your customized model, you can delete the deployment and m
 
 You can use various methods to delete the deployment for your customized model:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-model-deployment)</a>
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-model-deployment)</a>
 - The [Azure CLI](/cli/azure/cognitiveservices/account/deployment?preserve-view=true#az-cognitiveservices-account-deployment-delete)
 
 ### Delete your customized model
 
 Similarly, you can use various methods to delete your customized model:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-customized-model)
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-customized-model)
 
 > [!NOTE]
 > You can't delete a customized model if it has an existing deployment. You must first [delete your model deployment](#delete-your-model-deployment) before you can delete your customized model.
@@ -672,7 +672,7 @@ Similarly, you can use various methods to delete your customized model:
 
 You can optionally delete training and validation files that you uploaded for training, and result files generated during training, from your Azure OpenAI subscription. You can use the following methods to delete your training, validation, and result files:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-training-files)
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-training-files)
 - The [REST APIs](/rest/api/azureopenai/files/delete)
 - The Python SDK
 
diff --git a/articles/ai-services/openai/includes/fine-tuning-rest.md b/articles/ai-services/openai/includes/fine-tuning-rest.md
@@ -400,14 +400,14 @@ When you're done with your customized model, you can delete the deployment and m
 
 You can use various methods to delete the deployment for your customized model:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-model-deployment)
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-model-deployment)
 - The [Azure CLI](/cli/azure/cognitiveservices/account/deployment?view=azure-cli-latest&preserve-view=true#az-cognitiveservices-account-deployment-delete)
 
 ### Delete your customized model
 
 Similarly, you can use various methods to delete your customized model:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-customized-model)
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-customized-model)
 
 > [!NOTE]
 > You can't delete a customized model if it has an existing deployment. You must first [delete your model deployment](#delete-your-model-deployment) before you can delete your customized model.
@@ -416,7 +416,7 @@ Similarly, you can use various methods to delete your customized model:
 
 You can optionally delete training and validation files that you uploaded for training, and result files generated during training, from your Azure OpenAI subscription. You can use the following methods to delete your training, validation, and result files:
 
-- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=programming-language-ai-studio#delete-your-training-files)
+- [Azure AI Foundry](../how-to/fine-tuning.md?pivots=ai-foundry-portal#delete-your-training-files)
 
 ## Continuous fine-tuning
 
diff --git a/articles/ai-services/openai/realtime-audio-quickstart.md b/articles/ai-services/openai/realtime-audio-quickstart.md
@@ -9,7 +9,7 @@ ms.date: 10/3/2024
 author: eric-urban
 ms.author: eur
 ms.custom: references_regions, ignite-2024
-zone_pivot_groups: openai-studio-js
+zone_pivot_groups: openai-portal-js
 recommendations: false
 ---
 
@@ -58,7 +58,7 @@ Now that you have a deployment of the `gpt-4o-realtime-preview` model, you can i
 > [!TIP]
 > Right now, the fastest way to get started development with the GPT-4o Realtime API is to download the sample code from the [Azure OpenAI GPT-4o real-time audio repository on GitHub](https://github.com/azure-samples/aoai-realtime-audio-sdk).
 
-::: zone pivot="programming-language-ai-studio"
+::: zone pivot="ai-foundry-portal"
 
 To chat with your deployed `gpt-4o-realtime-preview` model in the [Azure AI Foundry](https://ai.azure.com) **Real-time audio** playground, follow these steps:
 
diff --git a/articles/ai-services/openai/use-your-data-quickstart.md b/articles/ai-services/openai/use-your-data-quickstart.md
@@ -2,7 +2,6 @@
 title: 'Use your own data with Azure OpenAI Service'
 titleSuffix: Azure OpenAI
 description: Use this article to import and use your data in Azure OpenAI.
-#services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.custom: devx-track-dotnet, devx-track-extended-java, devx-track-js, devx-track-ts, devx-track-go, devx-track-python
@@ -18,8 +17,7 @@ zone_pivot_groups: openai-use-your-data
 
 In this quickstart, you can use your own data with Azure OpenAI models. Using Azure OpenAI's models on your data can provide you with a powerful conversational AI platform that enables faster and more accurate communication.
 
-::: zone pivot="programming-language-studio"
-
+::: zone pivot="ai-foundry-portal"
 
 ## Prerequisites
 
diff --git a/articles/ai-services/openai/whats-new.md b/articles/ai-services/openai/whats-new.md
@@ -144,7 +144,7 @@ OpenAI has incorporated additional safety measures into the `o1` models, includi
 
 ### Availability
 
-The `o1-preview` and `o1-mini` are available in the East US2 region for limited access through the [AI Foundry](https://ai.azure.com) early access playground. Data processing for the `o1` models might occur in a different region than where they are available for use.
+The `o1-preview` and `o1-mini` are available in the East US2 region for limited access through the [AI Foundry portal](https://ai.azure.com) early access playground. Data processing for the `o1` models might occur in a different region than where they are available for use.
 
 To try the `o1-preview` and `o1-mini` models in the early access playground **registration is required, and access will be granted based on Microsoft’s eligibility criteria.**
 
diff --git a/articles/ai-services/speech-service/custom-speech-ai-foundry-portal.md b/articles/ai-services/speech-service/custom-speech-ai-foundry-portal.md
@@ -1,7 +1,7 @@
 ---
 title: Customize a speech model with fine-tuning in Azure AI Foundry portal
 titleSuffix: Azure AI services
-description: Learn about how to customize a speech model with fine-tuning in Azure AI Foundry portal.
+description: Learn about how to customize a speech model with fine-tuning in the Azure AI Foundry portal.
 author: eric-urban
 manager: nitinme
 ms.service: azure-ai-speech
@@ -18,9 +18,9 @@ ms.author: eur
 With custom speech, you can enhance speech recognition accuracy for your applications by using a custom model for real-time speech to text, speech translation, and batch transcription. The base model, trained with Microsoft-owned data, handles common spoken language well, but a custom model can improve domain-specific vocabulary and audio conditions by providing text and audio data for training. Additionally, you can train the model with structured text for custom pronunciations, display text formatting, and profanity filtering.
 
 > [!TIP]
-> You can bring your custom speech models from [Speech Studio](https://speech.microsoft.com) to [AI Foundry](https://ai.azure.com). In AI Foundry, you can pick up where you left off by connecting to your existing Speech resource. For more information about connecting to an existing Speech resource, see [Connect to an existing Speech resource](../../ai-studio/ai-services/how-to/connect-ai-services.md#connect-azure-ai-services-after-you-create-a-project).
+> You can bring your custom speech models from [Speech Studio](https://speech.microsoft.com) to [AI Foundry portal](https://ai.azure.com). In AI Foundry, you can pick up where you left off by connecting to your existing Speech resource. For more information about connecting to an existing Speech resource, see [Connect to an existing Speech resource](../../ai-studio/ai-services/how-to/connect-ai-services.md#connect-azure-ai-services-after-you-create-a-project).
 
-In [AI Foundry](https://ai.azure.com), you create a custom speech model by fine-tuning an Azure AI Speech base model with your own data. You can upload your data, test and train a custom model, compare accuracy between models, and deploy a model to a custom endpoint.
+In [AI Foundry portal](https://ai.azure.com), you create a custom speech model by fine-tuning an Azure AI Speech base model with your own data. You can upload your data, test and train a custom model, compare accuracy between models, and deploy a model to a custom endpoint.
 
 This article shows you how to use fine-tuning in AI Foundry to create a custom speech model. For more information about custom speech, see the [custom speech overview](./custom-speech-overview.md) documentation.
 
diff --git a/articles/ai-services/speech-service/language-support.md b/articles/ai-services/speech-service/language-support.md
@@ -33,7 +33,7 @@ Language support varies by Speech service functionality.
 
 # [Speech to text](#tab/stt)
 
-The table in this section summarizes the locales supported for speech to text. For details, see the table footnotes.
+The table in this section summarizes the locales supported for speech to text ([real-time](speech-to-text.md#real-time-speech-to-text) and [batch](speech-to-text.md#batch-transcription-api) transcription). 
 
 More remarks for speech to text locales are included in the [custom speech](#custom-speech) section of this article. 
 
diff --git a/articles/ai-services/speech-service/pronunciation-assessment-tool.md b/articles/ai-services/speech-service/pronunciation-assessment-tool.md
@@ -22,7 +22,7 @@ Pronunciation assessment uses the speech to text capability to provide subjectiv
 > [!NOTE]
 > For information about availability of pronunciation assessment, see [supported languages](language-support.md?tabs=pronunciation-assessment) and [available regions](regions.md#speech-service).
 
-This article describes how to use the pronunciation assessment tool without writing any code through the [AI Foundry](https://ai.azure.com/explore/aiservices/speech/pronunciationassessment). For information about how to integrate pronunciation assessment in your speech applications, see [How to use pronunciation assessment](how-to-pronunciation-assessment.md).
+This article describes how to use the pronunciation assessment tool without writing any code through the [AI Foundry portal](https://ai.azure.com/explore/aiservices/speech/pronunciationassessment). For information about how to integrate pronunciation assessment in your speech applications, see [How to use pronunciation assessment](how-to-pronunciation-assessment.md).
 
 
 ## Reading and speaking scenarios
@@ -35,7 +35,7 @@ For pronunciation assessment, there are two scenarios: Reading and Speaking.
 
 Follow these steps to assess your pronunciation of the reference text:
 
-1. Go to **Pronunciation assessment** in the [AI Foundry](https://ai.azure.com/explore/aiservices/speech).
+1. Go to **Pronunciation assessment** in the [AI Foundry portal](https://ai.azure.com/explore/aiservices/speech).
 
    :::image type="content" source="media/pronunciation-assessment/pronunciation-assessment-select.png" alt-text="Screenshot of how to go to Pronunciation assessment in AI Foundry.":::
 
@@ -57,7 +57,7 @@ Follow these steps to assess your pronunciation of the reference text:
 
 If you want to conduct an unscripted assessment, select the Speaking tab. This feature allows you to conduct unscripted assessment without providing reference text in advance. Here's how to proceed:
 
-1. Go to **Pronunciation assessment** in the [AI Foundry](https://ai.azure.com/explore/aiservices/speech).
+1. Go to **Pronunciation assessment** in the [AI Foundry portal](https://ai.azure.com/explore/aiservices/speech).
 
 1. On the Speaking tab, choose a supported [language](language-support.md?tabs=pronunciation-assessment) that you want to evaluate the pronunciation.
    
diff --git a/articles/ai-services/speech-service/toc.yml b/articles/ai-services/speech-service/toc.yml
@@ -59,7 +59,7 @@ items:
         - name: Custom speech overview
           href: custom-speech-overview.md
         - name: Fine-tune in the Azure AI Foundry portal
-          href: custom-speech-ai-studio.md
+          href: custom-speech-ai-foundry-portal.md
         - name: Create a custom speech model 
           items:
           - name: "Part 1: Create a project"
diff --git a/articles/ai-services/speech-service/~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md b/articles/ai-services/speech-service/~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md
diff --git a/articles/ai-studio/toc.yml b/articles/ai-studio/toc.yml
@@ -84,7 +84,7 @@ items:
       - name: Hear and speak with chat in the playground
         href: quickstarts/hear-speak-playground.md
       - name: Fine-tune in AI Foundry portal for custom speech
-        href: ../ai-services/speech-service/custom-speech-ai-studio.md?context=/azure/ai-studio/context/context
+        href: ../ai-services/speech-service/custom-speech-ai-foundry-portal.md?context=/azure/ai-studio/context/context
   - name: Explore and select AI models
     items:
     - name: Model catalog
diff --git a/zone-pivots/zone-pivot-groups.yml b/zone-pivots/zone-pivot-groups.yml

Original file line number	Diff line number	Diff line change
`@@ -22,9 +22,9 @@ Get started using GPT-4 Turbo with images with the Azure OpenAI Service.`
`22`	`22`	`>`
`23`	`23`	> The latest vision-capable models are `gpt-4o` and `gpt-4o mini`. These are in public preview. The latest available GA model is `gpt-4` version `turbo-2024-04-09`.
`24`	`24`
`25`		`-::: zone pivot="programming-language-studio"`
	`25`	`+::: zone pivot="ai-foundry-portal"`
`26`	`26`
`27`		`-[!INCLUDE [Studio quickstart](includes/gpt-v-studio.md)]`
	`27`	`+[!INCLUDE [AI Foundry portal quickstart](includes/gpt-v-studio.md)]`
`28`	`28`
`29`	`29`	`::: zone-end`
`30`	`30`