update

Author: laujan

articles/applied-ai-services/form-recognizer/concept-business-card.md

@@ -13,7 +13,7 @@ recommendations: false
 ---
 <!-- markdownlint-disable MD033 -->
 
-# Azure Form Recognizer Business Card model
+# Form Recognizer Business Card model
 
 The business card model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from business card images. The API analyzes printed business cards; extracts key information such as first name, last name, company name, email address, and phone number;  and returns a structured JSON data representation.
 
@@ -194,7 +194,7 @@ See how data, including name, job title, address, email, and company name, is ex
 
 ## Supported locales
 
-**Pre-built business cards v2.1** supports the following locales:
+**Prebuilt business cards v2.1** supports the following locales:
 
 * **en-us**
 * **en-au**
@@ -212,15 +212,15 @@ See how data, including name, job title, address, email, and company name, is ex
 
 ::: moniker range="form-recog-3.0.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 

articles/applied-ai-services/form-recognizer/concept-composed-models.md

@@ -41,12 +41,12 @@ With composed models, you can assign multiple custom models to a composed model
 
 ### Composed model compatibility
 
-|Custom model type|Models trained with v2.1 and v2.0| Custom template models v3.0 (preview)|Custom neural models v3.0 (preview)|Custom neural models 3.0 (GA)|
+|Custom model type|Models trained with v2.1 and v2.0| Custom template models v3.0 |Custom neural models v3.0 |Custom neural models 3.0 (GA)|
 |--|--|--|--|--|
 |**Models trained with version 2.1 and v2.0** |Supported|Supported|Not Supported|Not Supported|
-|**Custom template models v3.0 (preview)** |Supported|Supported|Not Supported|NotSupported|
+|**Custom template models v3.0** |Supported|Supported|Not Supported|NotSupported|
 |**Custom template models v3.0 (GA)** |Not Supported|Not Supported|Supported|Not Supported|
-|**Custom neural models v3.0 (preview)**|Not Supported|Not Supported|Supported|Not Supported|
+|**Custom neural models v3.0**|Not Supported|Not Supported|Supported|Not Supported|
 |**Custom Neural models v3.0 (GA)**|Not Supported|Not Supported|Not Supported|Supported|
 
 * To compose a model trained with a prior version of the API (v2.1 or earlier), train a model with the v3.0 API using the same labeled dataset. That addition will ensure that the v2.1 model can be composed with other models.

articles/applied-ai-services/form-recognizer/concept-custom.md

@@ -16,7 +16,7 @@ recommendations: false
 
 [!INCLUDE [applies to v3.0 and v2.1](includes/applies-to-v3-0-and-v2-1.md)]
 
-Form Recognizer uses advanced machine learning technology to detect and extract information from forms and documents and returns the extracted data in a structured JSON output. With Form Recognizer, you can use pre-built or pre-trained models or you can train standalone custom models. Custom models extract and analyze distinct data and use cases from forms and documents specific to your business. Standalone custom models can be combined to create [composed models](concept-composed-models.md).
+Form Recognizer uses advanced machine learning technology to detect and extract information from forms and documents and returns the extracted data in a structured JSON output. With Form Recognizer, you can use prebuilt or pre-trained models or you can train standalone custom models. Custom models extract and analyze distinct data and use cases from forms and documents specific to your business. Standalone custom models can be combined to create [composed models](concept-composed-models.md).
 
 To create a custom model, you label a dataset of documents with the values you want extracted and train the model on the labeled dataset. You only need five examples of the same form or document type to get started.
 

articles/applied-ai-services/form-recognizer/concept-form-recognizer-studio.md

@@ -33,7 +33,7 @@ The following Form Recognizer service features are available in the Studio.
 
 * **General Documents**: Try out Form Recognizer's General Documents feature to extract key-value pairs and entities. Start with the [Studio General Documents feature](https://formrecognizer.appliedai.azure.com/studio/document). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [General Documents overview](concept-general-document.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#general-document-model).
 
-* **Prebuilt models**: Form Recognizer's pre-built models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. As an example, start with the [Studio Invoice feature](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice). Explore with sample documents and your documents. Use the interactive visualization, extracted fields list, and JSON output to understand how the feature works. See the [Models overview](concept-model-overview.md) to learn more and get started with the [Python SDK quickstart for Prebuilt Invoice](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#prebuilt-model).
+* **Prebuilt models**: Form Recognizer's prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. As an example, start with the [Studio Invoice feature](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice). Explore with sample documents and your documents. Use the interactive visualization, extracted fields list, and JSON output to understand how the feature works. See the [Models overview](concept-model-overview.md) to learn more and get started with the [Python SDK quickstart for Prebuilt Invoice](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#prebuilt-model).
 
 * **Custom models**: Form Recognizer's custom models enable you to extract fields and values from models trained with your data, tailored to your forms and documents. Create standalone custom models or combine two or more custom models to create a composed model to extract data from multiple form types. Start with the [Studio Custom models feature](https://formrecognizer.appliedai.azure.com/studio/custommodel/projects).  Use the online wizard, labeling interface, training step, and visualizations to understand how the feature works. Test the custom model with your sample documents and iterate to improve the model. See the [Custom models overview](concept-custom.md) to learn more and use the [Form Recognizer v3.0 migration guide](v3-migration-guide.md) to start integrating the new models with your applications.
 

articles/applied-ai-services/form-recognizer/concept-general-document.md

@@ -14,7 +14,7 @@ recommendations: false
 ---
 <!-- markdownlint-disable MD033 -->
 
-# Azure Form Recognizer general document model
+# Form Recognizer general document model
 
 **This article applies to:** ![Form Recognizer v3.0 checkmark](media/yes-icon.png) **Form Recognizer v3.0**.
 

articles/applied-ai-services/form-recognizer/concept-id-document.md

@@ -14,9 +14,7 @@ ms.custom: references.regions
 ---
 <!-- markdownlint-disable MD033 -->
 
-# Azure Form Recognizer Identity document (ID) model
-
-The Form Recognizer Identity document (ID) model combines Optical Character Recognition (OCR) with deep learning models to analyze and extract key information from identity documents: US Drivers Licenses (all 50 states and District of Columbia), international passport biographical pages, US state IDs, social security cards, and permanent resident cards and more. The API analyzes identity documents, extracts key information, and returns a structured JSON data representation.
+# Form Recognizer identity document (ID) model
 
 ::: moniker range="form-recog-3.0.0"
 [!INCLUDE [applies to v3.0](includes/applies-to-v3-0.md)]
@@ -26,9 +24,13 @@ The Form Recognizer Identity document (ID) model combines Optical Character Reco
 [!INCLUDE [applies to v2.1](includes/applies-to-v2-1.md)]
 ::: moniker-end
 
-## Identity document (ID) processing
+Azure Form Recognizer Identity document (ID) model combines Optical Character Recognition (OCR) with deep learning models to analyze and extract key information from identity documents: US Drivers Licenses (all 50 states and District of Columbia), international passport biographical pages, US state IDs, social security cards, and permanent resident cards and more. The API analyzes identity documents, extracts key information, and returns a structured JSON data representation.
+
+## Identity document processing
+
+Identity document processing involves extracting data from identity documents either manually or by using OCR based techniques. Examples of identity documents include passports, driver licenses, resident cards, and national identity cards like the US social security card.
 
-Identity document (ID) processing involves extraction of data from identity documents whether manually or using OCR based techniques. Examples of identity documents include passports, driver licenses, resident cards, and national identity cards like the social security card in the US. It's an important step in any business process that requires some proof of identity. Examples include customer verification in banks and other financial institutions, mortgage applications, medical visits, claim processing, hospitality industry, and more. Individuals provide some proof of their identity via driver licenses, passports, and other similar documents so that the business can efficiently verify them before providing services and benefits.
+ID document processing an important step in any business process that requires some proof of identity. Examples include customer verification in banks and other financial institutions, mortgage applications, medical visits, claim processing, hospitality industry, and more. Individuals provide some proof of their identity via driver licenses, passports, and other similar documents so that the business can efficiently verify them before providing services and benefits.
 
 ::: moniker range="form-recog-3.0.0"
 
@@ -73,9 +75,13 @@ The following tools are supported by Form Recognizer v2.1:
 |**ID document model**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/prebuilts-analyze)</li><li>[**REST API**](/azure/applied-ai-services/form-recognizer/how-to-guides/use-sdk-rest-api?view=form-recog-2.1.0&preserve-view=true&tabs=windows&pivots=programming-language-rest-api#analyze-identity-id-documents)</li><li>[**Client-library SDK**](/azure/applied-ai-services/form-recognizer/how-to-guides/v2-1-sdk-rest-api)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=id-document#run-the-container-with-the-docker-compose-up-command)</li></ul>|
 ::: moniker-end
 
+## Input requirements
+
+[!INCLUDE [input requirements](./includes/input-requirements.md)]
+
 ### Try Form Recognizer
 
-Extract data, including name, birth date, machine-readable zone, and expiration date, from ID documents using the Form Recognizer Studio. You'll need the following resources:
+Extract data, including name, birth date, and expiration date, from ID documents. You'll need the following resources:
 
 * An Azure subscription—you can [create one for free](https://azure.microsoft.com/free/cognitive-services/)
 
@@ -145,10 +151,6 @@ Extract data, including name, birth date, machine-readable zone, and expiration
     * The "documentResults" field contains key/value pairs information and line items information for the most relevant parts of the document.
 ::: moniker-end
 
-## Input requirements
-
-[!INCLUDE [input requirements](./includes/input-requirements.md)]
-
 ::: moniker range="form-recog-3.0.0"
 
 ## Supported languages and locales
@@ -301,7 +303,7 @@ Below are the fields extracted per document type. The Azure Form Recognizer ID m
 
 ## Supported document types and locales
 
- **Pre-built ID v2.1** extracts key values from worldwide passports, and U.S. Driver's Licenses in the **en-us** locale.
+ **Prebuilt ID v2.1** extracts key values from worldwide passports, and U.S. Driver's Licenses in the **en-us** locale.
 
 ## Fields extracted
 
@@ -330,15 +332,15 @@ Below are the fields extracted per document type. The Azure Form Recognizer ID m
 
 ::: moniker range="form-recog-3.0.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 

articles/applied-ai-services/form-recognizer/concept-invoice.md

@@ -13,7 +13,7 @@ recommendations: false
 ---
 <!-- markdownlint-disable MD033 -->
 
-# Azure Form Recognizer invoice model
+# Form Recognizer invoice model
 
 ::: moniker range="form-recog-3.0.0"
 [!INCLUDE [applies to v3.0](includes/applies-to-v3-0.md)]
@@ -216,7 +216,7 @@ Keys can also exist in isolation when the model detects that a key exists, with
 
 ## Supported locales
 
-**Pre-built invoice v2.1** supports invoices in the **en-us** locale.
+**Prebuilt invoice v2.1** supports invoices in the **en-us** locale.
 
 ## Fields extracted
 
@@ -283,15 +283,15 @@ The JSON output has three parts:
 
 ::: moniker range="form-recog-3.0.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 

articles/applied-ai-services/form-recognizer/concept-layout.md

@@ -12,7 +12,7 @@ ms.author: lajanuar
 recommendations: false
 ---
 
-# Azure Form Recognizer layout model
+# Form Recognizer layout model
 
 The Form Recognizer Layout is an advanced machine-learning based document layout analysis model available in the Form Recognizer cloud API. In the version v2.1, the document layout model extracted text lines, words, tables, and selection marks.
 
@@ -404,15 +404,15 @@ Layout API also extracts selection marks from documents. Extracted selection mar
 
 ::: moniker range="form-recog-3.0.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 

articles/applied-ai-services/form-recognizer/concept-model-overview.md

@@ -333,15 +333,15 @@ A composed model is created by taking a collection of custom models and assignin
 
 ::: moniker range="form-recog-3.0.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.