add jan updates

Author: laujan

articles/ai-services/content-understanding/audio/overview.md

@@ -10,7 +10,7 @@ ms.topic: overview
 ms.date: 05/19/2025
 ---
 
-# Content Understanding audio solutions (preview)
+# Azure AI Content Understanding audio solutions (preview)
 
 > [!IMPORTANT]
 > * Azure AI Content Understanding is available in preview. Public preview releases provide early access to features that are in active development.
@@ -33,7 +33,7 @@ Content Understanding serves as a cornerstone for Speech Analytics solutions, en
 
 ### Content extraction
 
-Audio content extraction is the process of isolating and retrieving specific elements or features from an audio file. This process can include separating individual audio sources; identifying specific segments within a sound file; or detecting and categorizing various characteristics of the audio content.
+Audio content extraction is the process of transcribing audio files. This process includes separating transcriptions by speaker and can involve optional features like role detection to update speaker results to meaningful speaker roles. It can also involve detailed results including word-level timestamps.
 
 #### Language handling
 We support different options to handle language processing during transcription.
@@ -59,8 +59,8 @@ For languages with Fast transcriptions support and for files ≤ 300 MB and/or 
 * **Multilingual transcription**. Generates multilingual transcripts, applying language/locale per phrase. Deviating from language detection this feature is enabled when no language/locale is specified or language is set to `auto`.
 
 > [!NOTE]
-> When Multilingual transcription is used, a file with an unsupported locale produces a result. This result is based on the closest locale but most likely not correct.
-> This result is a known behavior. Make sure to configure locales when not using Multilingual transcription!
+> When Multilingual transcription is used, any files with unsupported locales produce a result based on the closest supported locale, which is likely incorrect. This result is a known
+> behavior. Avoid transcription quality issues by ensuring that you configure locales when not using a multilingual transcription supported locale!
 
 * **Language detection**. Automatically detects the dominant language/locale which is used to transcribe the file. Set multiple languages/locales to enable language detection.
 

articles/ai-services/content-understanding/concepts/analyzer-templates.md

@@ -10,7 +10,7 @@ ms.topic: overview
 ms.date: 05/19/2025
 ---
 
-# Analyzer templates offered with Content Understanding
+# Analyzer templates offered with Azure AI Content Understanding
 
 Content Understanding analyzer templates give you a head start in developing your Content Understanding solution by allowing you to build your analyzer without creating schemas from scratch.
 There are analyzer templates specific to common scenarios in each modality, such as call center audio analytics and advertising analysis for videos. Templates are also fully customizable, allowing you to adjust any

articles/ai-services/content-understanding/concepts/best-practices.md

@@ -10,7 +10,7 @@ ms.topic: overview
 ms.date: 05/19/2025
 ---
 
-# Best practices for Content Understanding
+# Best practices for Azure AI Content Understanding
 
 Azure AI Content Understanding is an innovative Generative AI service designed to facilitate the precise and accurate analysis of extensive data sets. The service processes various content modalities, including documents, images, videos, and audio, transforming them into user-specified output formats.
 

articles/ai-services/content-understanding/concepts/classifier.md

@@ -10,7 +10,7 @@ ms.topic: overview
 ms.date: 05/19/2025
 ---
 
-# Content Understanding classifier
+# Azure AI Content Understanding classifier
 
 > [!IMPORTANT]
 >

articles/ai-services/content-understanding/concepts/retrieval-augmented-generation.md

@@ -9,7 +9,7 @@ ms.service: azure-ai-content-understanding
 ms.topic: overview
 ms.date: 05/19/2025
 ---
-# Multimodal retrieval-augmented generation with Content Understanding
+# Multimodal retrieval-augmented generation with Azure AI Content Understanding
 
 Retrieval-augmented Generation (**RAG**) is a method that enhances the capabilities of Large Language Models (**LLM**) by integrating data from external knowledge sources. Integrating diverse and current information refines the precision and contextual relevance of the outputs generated by an **LLM**. A key challenge for **RAG** is the efficient extraction and processing of multimodal content—such as documents, images, audio, and video—to ensure accurate retrieval and effective use to bolster the **LLM** responses.
 

articles/ai-services/content-understanding/document/overview.md

@@ -10,7 +10,7 @@ ms.topic: overview
 ms.date: 05/19/2025
 ---
 
-# Content Understanding document solutions (preview)
+# Azure AI Content Understanding document solutions (preview)
 
 > [!IMPORTANT]
 >

articles/ai-services/content-understanding/glossary.md

@@ -10,7 +10,7 @@ ms.date: 05/19/2025
 ms.author: lajanuar
 ---
 
-# Content understanding terminologies
+# Azure AI Content Understanding terminologies
 
 | Term | Description |
 |:---------|:----------|

articles/ai-services/content-understanding/image/overview.md

@@ -10,7 +10,7 @@ ms.topic: how-to
 ms.date: 05/19/2025
 ---
 
-# Content Understanding image solutions (preview)
+# Azure AI Content Understanding image solutions (preview)
 
 > [!IMPORTANT]
 >

articles/ai-services/content-understanding/language-region-support.md

@@ -11,7 +11,7 @@ ms.custom: references_regions, ignite-2024-understanding-release
 ms.date: 05/19/2025
 ---
 
-# Content Understanding region and language support
+# Azure AI Content Understanding region and language support
 
 Azure AI Content Understanding provides multilingual support in multiple geographic regions to enable users to communicate with Content Understanding applications in natural ways and empower global outreach. The following sections describe the available regions and supported languages/locales.
 
@@ -34,7 +34,10 @@ Content Understanding applies [Azure OpenAI models](../openai/overview.md) which
 
 ### Text optical character recognition (OCR)
 
-The following table lists the supported languages/locales for **printed** text.
+> [!IMPORTANT]
+>
+> * The following list of supported languages have locale-aware normalization for words enabled in post-processing.
+> * Content Understanding supports different languages so we encourage you to try it out and focus on the content and not the value itself.
 
   |**Language**| **Language code**|**Language**| **Language code**|
   |:-----|:-----|:-----|:-----|

articles/ai-services/content-understanding/quickstart/use-ai-foundry.md

@@ -9,7 +9,7 @@ ms.topic: quickstart
 ms.date: 05/19/2025
 ---
 
-# Use Content Understanding in the Azure AI Foundry
+# Use Azure AI Content Understanding in the Azure AI Foundry
 
 [The Azure AI Foundry](https://aka.ms/cu-landing) is a comprehensive platform for developing and deploying generative AI applications and APIs responsibly. Azure AI Content Understanding is a new generative [Azure AI Service](../../what-are-ai-services.md) that analyzes files from varied modalities and extracts structured output in a user-defined field format. Input sources include document, video, image, and audio data. This guide shows you how to build and test a Content Understanding analyzer in the AI Foundry. You can then utilize the extracted data in any app or process you build using a simple REST API call. Content Understanding analyzers are fully customizable. You can create an analyzer by building your own schema from scratch or by using a suggested analyzer template offered to address common scenarios across each data type.