Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into ml-upgrade

Author: maud-lv

.openpublishing.redirection.json

@@ -10640,11 +10640,6 @@
             "redirect_url": "/azure/orbital/overview",
             "redirect_document_id": false
         },
-        {
-            "source_path_from_root": "/articles/load-balancer/cross-region-overview.md",
-            "redirect_url": "/azure/reliability/reliability-load-balancer",
-            "redirect_document_id": false
-        },
         {
             "source_path_from_root": "/articles/load-balancer/load-balancer-standard-availability-zones.md",
             "redirect_url": "/azure/reliability/reliability-load-balancer",

articles/ai-services/document-intelligence/concept-read.md

@@ -31,7 +31,7 @@ ms.author: lajanuar
 
 > [!NOTE]
 >
-> For extracting text from external images like labels, street signs, and posters, use the [Azure AI Vision v4.0 preview Read](../../ai-services/Computer-vision/concept-ocr.md) feature optimized for general, non-document images with a performance-enhanced synchronous API that makes it easier to embed OCR in your user experience scenarios.
+> For extracting text from external images like labels, street signs, and posters, use the [Azure AI Image Analysis v4.0 Read](../../ai-services/Computer-vision/concept-ocr.md) feature optimized for general, non-document images with a performance-enhanced synchronous API that makes it easier to embed OCR in your user experience scenarios.
 >
 
 Document Intelligence Read Optical Character Recognition (OCR) model runs at a higher resolution than Azure AI Vision Read and extracts print and handwritten text from PDF documents and scanned images. It also includes support for extracting text from Microsoft Word, Excel, PowerPoint, and HTML documents. It detects paragraphs, text lines, words, locations, and languages. The Read model is the underlying OCR engine for other Document Intelligence prebuilt models like Layout, General Document, Invoice, Receipt, Identity (ID) document, Health insurance card, W2 in addition to custom models.

articles/ai-services/document-intelligence/faq.yml

@@ -426,7 +426,7 @@ sections:
       - question: |
             How can I move my trained models from one environment (like beta) to another (like production)?
         answer: |
-            The Copy API enables this scenario by allowing you to copy custom models from one Document Intelligence account or into others, which can exist in any supported geographical region. Follow [this document](disaster-recovery.md) for detailed instructions. The copy operation is limited to copying models within the specific cloud environment the model was trained in. For instance, copying models from the public cloud to the Azure Government clod isn't supported.
+            The Copy API enables this scenario by allowing you to copy custom models from one Document Intelligence account or into others, which can exist in any supported geographical region. Follow [this document](disaster-recovery.md) for detailed instructions. The copy operation is limited to copying models within the specific cloud environment the model was trained in. For instance, copying models from the public cloud to the Azure Government cloud isn't supported.
 
       - question: |
           Why was I charged for Layout when running custom training?

articles/ai-services/language-service/native-document-support/use-native-documents.md

@@ -28,15 +28,15 @@ ms.author: lajanuar
 
 Azure AI Language is a cloud-based service that applies Natural Language Processing (NLP) features to text-based data. The native document support capability enables you to send API requests asynchronously, using an HTTP POST request body to send your data and HTTP GET request query string to retrieve the processed data.
 
-A native document refers to the file format used to create the original document such as Microsoft Word (docx) or a portable document file (pdf). Native document support eliminates the need for text preprocessing prior to using Azure AI Language resource capabilities.  Currently, native document support is available for the following capabilities:
+A native document refers to the file format used to create the original document such as Microsoft Word (docx) or a portable document file (pdf). Native document support eliminates the need for text preprocessing before using Azure AI Language resource capabilities. Currently, native document support is available for the following capabilities:
 
 * [Personally Identifiable Information (PII)](../personally-identifiable-information/overview.md). The PII detection feature can identify, categorize, and redact sensitive information in unstructured text. The `PiiEntityRecognition` API supports native document processing.
 
 * [Document summarization](../summarization/overview.md). Document summarization uses natural language processing to generate extractive (salient sentence extraction) or abstractive (contextual word extraction) summaries for documents. Both `AbstractiveSummarization` and `ExtractiveSummarization` APIs support native document processing.
 
 ## Supported document formats
 
- Applications use native file formats to create, save, or open native documents.  Currently **PII** and **Document summarization** capabilities supports the following native document formats:
+ Applications use native file formats to create, save, or open native documents. Currently **PII** and **Document summarization** capabilities supports the following native document formats:
 
 |File type|File extension|Description|
 |---------|--------------|-----------|
@@ -69,7 +69,7 @@ A native document refers to the file format used to create the original document
 
     > [!NOTE]
     > The cURL package is pre-installed on most Windows 10 and Windows 11 and most macOS and Linux distributions. You can check the package version with the following commands:
-    > Windows: `curl.exe -V`.
+    > Windows: `curl.exe -V`
     > macOS `curl -V`
     > Linux: `curl --version`
 
@@ -78,7 +78,7 @@ A native document refers to the file format used to create the original document
   * [Windows](https://curl.haxx.se/windows/).
   * [Mac or Linux](https://learn2torials.com/thread/how-to-install-curl-on-mac-or-linux-(ubuntu)-or-windows).
 
-* An active [**Azure account**](https://azure.microsoft.com/free/cognitive-services/).  If you don't have one, you can [**create a free account**](https://azure.microsoft.com/free/).
+* An active [**Azure account**](https://azure.microsoft.com/free/cognitive-services/). If you don't have one, you can [**create a free account**](https://azure.microsoft.com/free/).
 
 * An [**Azure Blob Storage account**](https://portal.azure.com/#create/Microsoft.StorageAccount-ARM). You also need to [create containers](#create-azure-blob-storage-containers) in your Azure Blob Storage account for your source and target files:
 
@@ -128,7 +128,7 @@ Your Language resource needs granted access to your storage account before it ca
 
 * [**Shared access signature (SAS) tokens**](shared-access-signatures.md). User delegation SAS tokens are secured with Microsoft Entra credentials. SAS tokens provide secure, delegated access to resources in your Azure storage account.
 
-* [**Managed identity role-based access control (RBAC)**](managed-identities.md). Managed identities for Azure resources are service principals that create a Microsoft Entra identity and specific permissions for Azure managed resources
+* [**Managed identity role-based access control (RBAC)**](managed-identities.md). Managed identities for Azure resources are service principals that create a Microsoft Entra identity and specific permissions for Azure managed resources.
 
 For this project, we authenticate access to the `source location` and `target location` URLs with Shared Access Signature (SAS) tokens appended as query strings. Each token is assigned to a specific blob (file).
 
@@ -177,7 +177,7 @@ For this quickstart, you need a **source document** uploaded to your **source co
                 "language": "en-US",
                 "id": "Output-excel-file",
                 "source": {
-                    "location": "{your-source-container-with-SAS-URL}"
+                    "location": "{your-source-blob-with-SAS-URL}"
                 },
                 "target": {
                     "location": "{your-target-container-with-SAS-URL}"
@@ -189,8 +189,8 @@ For this quickstart, you need a **source document** uploaded to your **source co
         {
             "kind": "PiiEntityRecognition",
             "parameters":{
-                "excludePiiCategoriesredac" : ["PersonType", "Category2", "Category3"],
-                "redactionPolicy": "UseEntityTypeName" 
+                "excludePiiCategories" : ["PersonType", "Category2", "Category3"],
+                "redactionPolicy": "UseRedactionCharacterWithRefId" 
             }
         }
     ]
@@ -344,7 +344,7 @@ For this project, you need a **source document** uploaded to your **source conta
         "documents":[
             {
           "source":{
-            "location":"{your-source-container-SAS-URL}"
+            "location":"{your-source-blob-SAS-URL}"
           },
           "targets":
             {

articles/ai-services/openai/reference.md

@@ -61,7 +61,7 @@ POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deploymen
 - `2023-08-01-preview` (retiring April 2, 2024) [Swagger spec](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-08-01-preview/inference.json)
 - `2023-09-01-preview` (retiring April 2, 2024) [Swagger spec](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-09-01-preview/inference.json)
 - `2023-12-01-preview` [Swagger spec](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview/inference.json)
-- `2024-02-15-preview`[Swagger spec](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2024-12-15-preview/inference.json)
+- `2024-02-15-preview`[Swagger spec](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2024-02-15-preview/inference.json)
 
 **Request body**
 

articles/ai-services/speech-service/how-to-pronunciation-assessment.md

@@ -621,15 +621,15 @@ The following table summarizes which features that locales support. For more spe
 
 | Phoneme alphabet | IPA     | SAPI |
 |:-----------------|:--------|:-----|
-| Phoneme name     | `en-US` | `en-US`, `en-GB`, `zh-CN` |
-| Syllable group   | `en-US` | `en-US`, `en-GB` |
-| Spoken phoneme   | `en-US` | `en-US`, `en-GB` |
+| Phoneme name     | `en-US` | `en-US`, `zh-CN` |
+| Syllable group   | `en-US` | `en-US`|
+| Spoken phoneme   | `en-US` | `en-US` |
 
 ### Syllable groups
 
 Pronunciation assessment can provide syllable-level assessment results. A word is typically pronounced syllable by syllable rather than phoneme by phoneme. Grouping in syllables is more legible and aligned with speaking habits.
 
-Pronunciation assessment supports syllable groups only in `en-US` with IPA and in both `en-US` and `en-GB` with SAPI.
+Pronunciation assessment supports syllable groups only in `en-US` with IPA and with SAPI.
 
 The following table compares example phonemes with the corresponding syllables.
 
@@ -644,7 +644,7 @@ To request syllable-level results along with phonemes, set the granularity [conf
 
 ### Phoneme alphabet format
 
-Pronunciation assessment supports phoneme name in `en-US` with IPA and in `en-US`, `en-GB` and `zh-CN` with SAPI.
+Pronunciation assessment supports phoneme name in `en-US` with IPA and in `en-US` and `zh-CN` with SAPI.
 
 For locales that support phoneme name, the phoneme name is provided together with the score. Phoneme names help identify which phonemes were pronounced accurately or inaccurately. For other locales, you can only get the phoneme score.
 
@@ -722,7 +722,7 @@ pronunciationAssessmentConfig?.phonemeAlphabet = "IPA"
 
 With spoken phonemes, you can get confidence scores that indicate how likely the spoken phonemes matched the expected phonemes.
 
-Pronunciation assessment supports spoken phonemes in `en-US` with IPA and in both `en-US` and `en-GB` with SAPI.
+Pronunciation assessment supports spoken phonemes in `en-US` with IPA and with SAPI.
 
 For example, to obtain the complete spoken sound for the word `Hello`, you can concatenate the first spoken phoneme for each expected phoneme with the highest confidence score. In the following assessment result, when you speak the word `hello`, the expected IPA phonemes are `h ɛ l oʊ`. However, the actual spoken phonemes are `h ə l oʊ`. You have five possible candidates for each expected phoneme in this example. The assessment result shows that the most likely spoken phoneme was `ə` instead of the expected phoneme `ɛ`. The expected phoneme `ɛ` only received a confidence score of 47. Other potential matches received confidence scores of 52, 17, and 2.
 

articles/ai-services/speech-service/personal-voice-how-to-use.md

@@ -47,6 +47,8 @@ Here's example SSML in a request for text to speech with the voice name and the
 You can use the SSML via the [Speech SDK](./get-started-text-to-speech.md), [REST API](rest-text-to-speech.md), or [batch synthesis API](batch-synthesis.md).
 
 * **Real-time speech synthesis**: Use the [Speech SDK](./get-started-text-to-speech.md) or [REST API](rest-text-to-speech.md) to convert text to speech.
+    * When you use Speech SDK, don't set Endpoint Id, just like prebuild voice.
+    * When you use REST API, please use prebuilt neural voices endpoint.
 
 * **Asynchronous synthesis of long audio**: Use the [batch synthesis API](batch-synthesis.md) (Preview) to asynchronously synthesize text to speech files longer than 10 minutes (for example, audio books or lectures). Unlike synthesis performed via the Speech SDK or Speech to text REST API, responses aren't returned in real-time. The expectation is that requests are sent asynchronously, responses are polled for, and synthesized audio is downloaded when the service makes it available.