Merge pull request #6008 from MicrosoftDocs/main

Auto Publish – main to live - 2025-07-12 05:00 UTC

Author: learn-build-service-prod[bot]

articles/ai-services/document-intelligence/how-to-guides/disaster-recovery.md

@@ -33,7 +33,7 @@ ms.author: lajanuar
 
 ::: moniker range=">= doc-intel-2.1.0"
 
-When you create a Document Intelligence resource in the Azure portal, you specify a region. From then on, your resource and all of its operations stay associated with that particular Azure server region. It's rare, but not impossible, to encounter a network issue that hits an entire region. If your solution needs to always be available, then you should design it to either fail-over into another region or split the workload between two or more regions. Both approaches require at least two Document Intelligence resources in different regions and the ability to sync custom models and classifiers across regions.
+When you create a Document Intelligence resource in the Azure portal, you specify a region. From then on, your resource and all of its operations stay associated with that particular Azure region. It's rare, but not impossible, to encounter a network issue that hits an entire region. If your solution needs to always be available, then you should design it to either fail-over into another region or split the workload between two or more regions. Both approaches require at least two Document Intelligence resources in different regions and the ability to sync custom models and classifiers across regions.
 
 The Copy API enables this scenario by allowing you to copy custom models and classifiers from one Document Intelligence account or into others, which can exist in any supported geographical region. This guide shows you how to use the Copy REST API with cURL for custom models. You can also use an HTTP request service to issue the requests.
 

articles/ai-services/speech-service/includes/release-notes/release-notes-cli.md

@@ -5,6 +5,21 @@ ms.topic: include
 ms.date: 08/01/2024
 ms.author: eur
 ---
+### Speech CLI 1.45.0: 2025-June release
+Updated to use Speech SDK 1.45.0
+#### New features
+* none
+#### Bug fixes
+* none
+
+### Speech CLI 1.44: 2025-May release
+
+#### New features
+  * Added support for authentication with Microsoft Entra token credentials.
+  * Added support for the Fast transcription API.
+  
+##### Bug fixes
+  * Fixed non-working semicolon-separated input URLs and input file/URL lists from a file.
 
 ### Speech CLI 1.43: 2025-March release
 

articles/ai-services/speech-service/includes/release-notes/release-notes-sdk.md

@@ -8,6 +8,25 @@ ms.author: eur
 
 > [!IMPORTANT]
 > Content assessment (preview) via the Speech SDK is being retired in July 2025. Instead, you can use Azure OpenAI models to get content assessment results as described in the [content assessment documentation](../../how-to-pronunciation-assessment.md#content-assessment).
+
+### Speech SDK 1.45: 2025-July release
+
+#### New features:
+  * Added support for setting the phrase list grammar weight. (Currently only effects embedded scenarios)
+  * Added more specific file opening error codes.
+  * Updated Unicode path support so that SDK Windows DLLs can be located under non-ASCII paths.
+  * Updated descriptions of segmentation strategy properties to align with the service logic.
+  * [C#, Java] Added support for authentication using ApiKeyCredential.
+  
+#### Bug fixes
+  * Fixed the Microsoft Audio Stack (MAS) initialization error about microphone geometry in certain regions.
+  * Fixed profanity settings not working in speech translation (https://github.com/Azure-Samples/cognitive-services-speech-sdk/issues/2856).
+  * Fixed a crash in intent recognition pattern matching with Japanese language.
+  * Fixed custom domain resolution not working with Node.js v22 or newer.
+
+#### Samples
+  * [Java ] Added sample code to demonstrate AAD token credential authentication.
+
 ### Speech SDK 1.44.1: Patch release
 
 SDK version 1.44.1 is being released for JavaScript only with 4 bug fixes:
@@ -66,16 +85,6 @@ SDK version 1.44.1 is being released for JavaScript only with 4 bug fixes:
 ##### Bug fixes
   * Fixed an infinite connection retry loop on unsupported connection closing codes (https://github.com/microsoft/cognitive-services-speech-sdk-js/issues/896).
 
-### Speech CLI (SPX)
-
-#### New features
-  * Added support for authentication with Microsoft Entra token credentials.
-  * Added support for the Fast transcription API.
-  
-##### Bug fixes
-  * Fixed non-working semicolon-separated input URLs and input file/URL lists from a file.
-
-
 ### Speech SDK 1.43: 2025-March release
 
 > [!NOTE]

articles/ai-services/speech-service/includes/release-notes/release-notes-stt.md

@@ -7,21 +7,27 @@ ms.author: eur
 ms.custom: references_regions
 ---
 
+### July 2025 release
+
+#### Improved speech to text models
+
+The English models (all `en-*` models except for `en-IN`) were updated to incorporate a new VAD (voice activity detector) which helps reduce the latency by 100 ms or more. It can affect the accuracy and silence segmentation both positively and negatively, with the aim of reducing latency. Further language expansion is coming in the next few months.
+
 ### June 2025 release
 
 #### Improved pronunciation assessment model
 
-We've rolled out significant upgrades to the pronunciation assessment models for `ta-IN` and `ms-MY`. You'll see a noticeable jump in Pearson Correlation Coefficients (PCC), which means more precise and dependable evaluations.
+We rolled out significant upgrades to the pronunciation assessment models for `ta-IN` and `ms-MY`. You're seeing a noticeable jump in Pearson Correlation Coefficients (PCC), which means more precise and dependable evaluations.
 
 These updated models are ready to use through the API and the Azure AI Foundry playground, just like before.
 
 #### Improved speech to text models
-Accuracy of speech to text models in [fast transcription](../../fast-transcription-create.md) for `de-DE`, `en-US`, `en-GB`, `es-ES`, `es-MX`,  `fr-FR`, `it-IT`, `ja-JP`, `ko-KR`, `pt-BR`, and `zh-CN` locales are improved by 10%-25% percent respectively, particularly with improved readaibility and recognition on entities.
+Accuracy of speech to text models in [fast transcription](../../fast-transcription-create.md) for `de-DE`, `en-US`, `en-GB`, `es-ES`, `es-MX`,  `fr-FR`, `it-IT`, `ja-JP`, `ko-KR`, `pt-BR`, and `zh-CN` locales improving by 10%-25% percent respectively, particularly with improved readability and recognition on entities.
 
 ### May 2025 release
 
 #### Improved speech to text models
-Accuracy of speech to text models for `ta-IN`, `te-IN`, `en-IN`, and `hu-HU` locales are improved by 5-10 percent respectively. We also approximate a 20x reduction in ghost words for the `ta-IN` and `te-IN` models.
+Accuracy of speech to text models for `ta-IN`, `te-IN`, `en-IN`, and `hu-HU` locales improving by 5-10 percent respectively. We also approximate a 20x reduction in ghost words for the `ta-IN` and `te-IN` models.
 
 #### Fast transcription API - Multi-lingual speech transcription
 

articles/search/.openpublishing.redirection.search.json

@@ -9,6 +9,16 @@
             "source_path_from_root": "/articles/search/cognitive-search-quickstart-blob.md",
             "redirect_url": "/azure/search/search-get-started-skillset",
             "redirect_document_id": true
+        },
+                {
+            "source_path_from_root": "/articles/search/cognitive-search-tutorial-blob.md",
+            "redirect_url": "/azure/search/tutorial-skillset",
+            "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/search/cognitive-search-tutorial-blob-dotnet.md",
+            "redirect_url": "/azure/search/tutorial-skillset",
+            "redirect_document_id": false
         },
         {
             "source_path_from_root": "/articles/search/search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md",

articles/search/chat-completion-skill-example-usage.md

@@ -117,7 +117,7 @@ This section supplements the [skill reference](cognitive-search-defining-skillse
 Once the basic framework of your skillset is created and Azure AI services is configured, you can focus on each individual image skill, defining inputs and source context, and mapping outputs to fields in either an index or knowledge store.
 
 > [!NOTE]
-> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](cognitive-search-tutorial-blob.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
+> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
 
 ### Example inputs for image processing
 

articles/search/cognitive-search-concept-image-scenarios.md

@@ -166,7 +166,7 @@ This section supplements the [skill reference](cognitive-search-predefined-skill
 Once the basic framework of your skillset is created and Azure AI services is configured, you can focus on each individual image skill, defining inputs and source context, and mapping outputs to fields in either an index or knowledge store.
 
 > [!NOTE]
-> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](cognitive-search-tutorial-blob.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
+> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
 
 ### Inputs for image processing
 

articles/search/cognitive-search-concept-intro.md

@@ -135,7 +135,7 @@ To repeat any of the above steps, [reset the indexer](search-howto-reindex.md) b
 ## Next steps
 
 + [Quickstart: Create a skillset for AI enrichment](search-get-started-skillset.md)
-+ [Tutorial: Learn about the AI enrichment REST APIs](cognitive-search-tutorial-blob.md)
++ [Tutorial: Learn about the AI enrichment REST APIs](tutorial-skillset.md)
 + [Skillset concepts](cognitive-search-working-with-skillsets.md)
 + [Knowledge store concepts](knowledge-store-concept-intro.md)
 + [Create a skillset](cognitive-search-defining-skillset.md)

articles/search/cognitive-search-concept-troubleshooting.md

@@ -71,7 +71,7 @@ For [parallel indexing](search-howto-large-index.md), distribute your data into
 ## See also
 
 + [Quickstart: Create an AI enrichment pipeline in the Azure portal](search-get-started-skillset.md)
-+ [Tutorial: Learn AI enrichment REST APIs](cognitive-search-tutorial-blob.md)
++ [Tutorial: Learn AI enrichment REST APIs](tutorial-skillset.md)
 + [How to configure blob indexers](search-howto-indexing-azure-blob-storage.md)
 + [How to define a skillset](cognitive-search-defining-skillset.md)
 + [How to map enriched fields to an index](cognitive-search-output-field-mapping.md)

articles/search/cognitive-search-predefined-skills.md

@@ -81,4 +81,4 @@ For guidance on creating a custom skill, see [Define a custom interface](cogniti
 
 + [How to define a skillset](cognitive-search-defining-skillset.md)
 + [Custom Skills interface definition](cognitive-search-custom-skill-interface.md)
-+ [Tutorial: Enriched indexing with AI](cognitive-search-tutorial-blob.md)
++ [Tutorial: Enriched indexing with AI](tutorial-skillset.md)