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articles/ai-services/openai/concepts/content-credentials.md

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ms.author: pafarley
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 11/08/2023
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ms.date: 8/28/2024
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manager: nitinme
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---
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articles/ai-services/openai/concepts/red-teaming.md

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description: Learn about how red teaming and adversarial testing are an essential practice in the responsible development of systems and features using large language models (LLMs)
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 09/20/2023
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ms.date: 11/30/2024
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manager: nitinme
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author: mrbullwinkle
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ms.author: mbullwin

articles/ai-services/speech-service/custom-speech-ai-foundry-portal.md

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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.
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> [!TIP]
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> 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).
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> You can bring your custom speech models from [Speech Studio](https://speech.microsoft.com) to the [Azure 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).
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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.
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1. Go to your AI Foundry project. If you need to create a project, see [Create an AI Foundry project](../../ai-studio/how-to/create-projects.md).
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1. Select **Fine-tuning** from the left pane.
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1. Select **AI Service fine-tuning**.
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1. Select **AI Service fine-tuning** > **+ Fine-tune**.
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:::image type="content" source="../../ai-studio/media/ai-services/fine-tune-azure-ai-services.png" alt-text="Screenshot of the page to select fine-tuning of Azure AI Services models." lightbox="../../ai-studio/media/ai-services/fine-tune-azure-ai-services.png":::
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articles/ai-studio/ai-services/how-to/connect-ai-services.md

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# How to use Azure AI services in AI Foundry portal
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You might have existing resources for Azure AI services that you used in the old studios such as Azure OpenAI Studio or Speech Studio. You can pick up where you left off by using your existing resources in AI Foundry portal.
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You might have existing resources for Azure AI services that you used in the old studios such as Azure OpenAI Studio or Speech Studio. You can pick up where you left off by using your existing resources in the [Azure AI Foundry portal](https://ai.azure.com).
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This article describes how to use new or existing Azure AI services resources in an AI Foundry project.
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## Bring your existing Azure AI services resources into a project
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Let's look at two ways to connect Azure AI services resources to a project:
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Let's look at two ways to connect Azure AI services resources to an Azure AI Foundry project:
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- [When you create a project](#connect-azure-ai-services-when-you-create-a-project-for-the-first-time)
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- [After you create a project](#connect-azure-ai-services-after-you-create-a-project)

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