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Copy file name to clipboardExpand all lines: articles/cognitive-services/Speech-Service/speech-container-howto.md
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ms.service: cognitive-services
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ms.subservice: speech-service
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ms.topic: conceptual
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ms.date: 04/29/2020
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ms.date: 05/05/2020
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ms.author: aahi
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---
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## Request access to the container registry
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Fill out and submit the [Cognitive Services Speech Containers Request form](https://aka.ms/speechcontainerspreview/) to request access to the container.
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Fill out and submit the [Cognitive Services containers request form](https://aka.ms/cognitivegate) to request access to the container.
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[!INCLUDE [Request access to the container registry](../../../includes/cognitive-services-containers-request-access-only.md)]
Copy file name to clipboardExpand all lines: articles/cognitive-services/cognitive-services-container-support.md
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Azure Cognitive Services containers provide the following set of Docker containers, each of which contains a subset of functionality from services in Azure Cognitive Services:
|[Anomaly detector][ad-containers]|F0, S0|**Anomaly-Detector**|The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning.<br>[Request access](https://aka.ms/adcontainer)|
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|[Computer Vision][cv-containers]|F0, S1|**Read**|Extracts printed text from images of various objects with different surfaces and backgrounds, such as receipts, posters, and business cards. The Read container also detects *handwritten text* in images and provides PDF/TIFF/multi-page support.<br/><br/>**Important:** The Read container currently works only with English.|
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|[Face][fa-containers]|F0, S0|**Face**|Detects human faces in images, and identifies attributes, including face landmarks (such as noses and eyes), gender, age, and other machine-predicted facial features. In addition to detection, Face can check if two faces in the same image or different images are the same by using a confidence score, or compare faces against a database to see if a similar-looking or identical face already exists. It can also organize similar faces into groups, using shared visual traits.<br>[Request access](Face/face-how-to-install-containers.md#request-access-to-the-private-container-registry)|
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|[Form recognizer][fr-containers]|F0, S0|**Form Recognizer**|Form Understanding applies machine learning technology to identify and extract key-value pairs and tables from forms.<br>[Request access](https://aka.ms/FormRecognizerContainerRequestAccess)|
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|[LUIS][lu-containers]|F0, S0|**LUIS** ([image](https://go.microsoft.com/fwlink/?linkid=2043204&clcid=0x409))|Loads a trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints. You can collect query logs from the container and upload these back to the [LUIS portal](https://www.luis.ai) to improve the app's prediction accuracy.|
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|[Speech Service API][sp-containers-stt]|F0, S0|**Speech-to-text**|Transcribes continuous real-time speech into text.|
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|[Speech Service API][sp-containers-cstt]|F0, S0|**Custom Speech-to-text**|Transcribes continuous real-time speech into text using a custom model.|
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|[Speech Service API][sp-containers-tts]|F0, S0|**Text-to-speech**|Converts text to natural-sounding speech.|
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|[Speech Service API][sp-containers-ctts]|F0, S0|**Custom Text-to-speech**|Converts text to natural-sounding speech using a custom model.|
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|[Text Analytics][ta-containers-keyphrase]|F0, S|**Key Phrase Extraction** ([image](https://go.microsoft.com/fwlink/?linkid=2018757&clcid=0x409)) |Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". |
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|[Text Analytics][ta-containers-language]|F0, S|**Language Detection** ([image](https://go.microsoft.com/fwlink/?linkid=2018759&clcid=0x409)) |For up to 120 languages, detects which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score. |
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|[Text Analytics][ta-containers-sentiment]|F0, S|**Sentiment Analysis** ([image](https://go.microsoft.com/fwlink/?linkid=2018654&clcid=0x409)) |Analyzes raw text for clues about positive or negative sentiment. This API returns a sentiment score between 0 and 1 for each document, where 1 is the most positive. The analysis models are pre-trained using an extensive body of text and natural language technologies from Microsoft. For [selected languages](./text-analytics/language-support.md), the API can analyze and score any raw text that you provide, directly returning results to the calling application. |
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|--|--|--|--|
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|[Anomaly detector][ad-containers]|F0, S0|**Anomaly-Detector**|The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning.<br>[Request access][request-access]|
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|[Computer Vision][cv-containers]|F0, S1|**Read**|Extracts printed text from images of various objects with different surfaces and backgrounds, such as receipts, posters, and business cards. The Read container also detects *handwritten text* in images and provides PDF/TIFF/multi-page support.<br/><br/>**Important:** The Read container currently works only with English.|
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|[Face][fa-containers]|F0, S0|**Face**|Detects human faces in images, and identifies attributes, including face landmarks (such as noses and eyes), gender, age, and other machine-predicted facial features. In addition to detection, Face can check if two faces in the same image or different images are the same by using a confidence score, or compare faces against a database to see if a similar-looking or identical face already exists. It can also organize similar faces into groups, using shared visual traits.<br>[Request access][request-access]|
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|[Form recognizer][fr-containers]|F0, S0|**Form Recognizer**|Form Understanding applies machine learning technology to identify and extract key-value pairs and tables from forms.<br>[Request access][request-access]|
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|[LUIS][lu-containers]|F0, S0|**LUIS** ([image](https://go.microsoft.com/fwlink/?linkid=2043204&clcid=0x409))|Loads a trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints. You can collect query logs from the container and upload these back to the [LUIS portal](https://www.luis.ai) to improve the app's prediction accuracy.|
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|[Speech Service API][sp-containers-stt]|F0, S0|**Speech-to-text**|Transcribes continuous real-time speech into text.|
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|[Speech Service API][sp-containers-cstt]|F0, S0|**Custom Speech-to-text**|Transcribes continuous real-time speech into text using a custom model.|
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|[Speech Service API][sp-containers-tts]|F0, S0|**Text-to-speech**|Converts text to natural-sounding speech.|
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|[Speech Service API][sp-containers-ctts]|F0, S0|**Custom Text-to-speech**|Converts text to natural-sounding speech using a custom model.|
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|[Text Analytics][ta-containers-keyphrase]|F0, S|**Key Phrase Extraction** ([image](https://go.microsoft.com/fwlink/?linkid=2018757&clcid=0x409)) |Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". |
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|[Text Analytics][ta-containers-language]|F0, S|**Language Detection** ([image](https://go.microsoft.com/fwlink/?linkid=2018759&clcid=0x409)) |For up to 120 languages, detects which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score. |
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|[Text Analytics][ta-containers-sentiment]|F0, S|**Sentiment Analysis v3** ([image](https://go.microsoft.com/fwlink/?linkid=2018654&clcid=0x409)) |Analyzes raw text for clues about positive or negative sentiment. This version of sentiment analysis returns sentiment labels (for example *positive* or *negative*) for each document and sentence within it. |
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<!--
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|[Personalizer](https://go.microsoft.com/fwlink/?linkid=2083923&clcid=0x409) |F0, S0|**Personalizer** ([image](https://go.microsoft.com/fwlink/?linkid=2083928&clcid=0x409))|Azure Personalizer is a cloud-based API service that allows you to choose the best experience to show to your users, learning from their real-time behavior.|
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Azure Cognitive Services containers are publicly available through your Azure subscription, and Docker container images can be pulled from either the Microsoft Container Registry or Docker Hub. You can use the [docker pull](https://docs.docker.com/engine/reference/commandline/pull/) command to download a container image from the appropriate registry.
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> [!IMPORTANT]
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> Currently, you must complete a sign-up process to access the following containers, in which you fill out and submit a questionnaire with questions about you, your company, and the use case for which you want to implement the containers. Once you're granted access and provided credentials, you can then pull the container images from a private container registry hosted by Azure Container Registry.
description: Learn how to apply for early access to new Cognitive Services containers and APIs.
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services: cognitive-services
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.topic: conceptual
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ms.date: 04/24/2020
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ms.author: aahi
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---
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# Gating process for Azure Cognitive Services
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> [!NOTE]
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> After a service offering completes a gated preview, it goes into an "ungated" public preview which does not require an application for access. After the preview process, it's released as Generally Available (GA).
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As new Azure Cognitive Services offerings are introduced, they go through a gated preview where customers have to request access through an application. This gating process helps identify opportunities for improvements to service offerings before they're widely available.
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This article will guide you through the application process for gated Cognitive Services offerings.
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## Eligibility and Approval process
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The gating process is in place to help gauge interest and better understand customer needs. The Microsoft team accepts [applications](https://forms.office.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbRyQZ7B8Cg2FEjpibPziwPcZUNlQ4SEVORFVLTjlBSzNLRlo0UzRRVVNPVy4u) from Microsoft commercial customers with a valid Azure subscription and a valid business scenario. Customers will potentially have their applications denied when:
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- They're not associated with any organization
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- They do not have a valid Azure subscription
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- The application was submitted through personal email (@hotmail.com, @gmail.com, @yahoo.com)
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- There was no proper justification or business scenario provided
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Given the demand from different customer segments, we're attempting to expedite approval process. However, we cannot commit to a timeline. Once a decision is made, the Microsoft team will contact you and your account management team for the next steps. We appreciate your understanding and patience.
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If the application is approved, the Microsoft team will send an email with details, documentation, and guidance. Cognitive Services pricing details available [here](https://azure.microsoft.com/pricing/details/cognitive-services/).
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Currently, the services below are offered through the gating process:
|[Form Recognizer][fr-containers]| Form Recognizer |
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|[Speech Service API][sp-containers]| Speech-to-text (Custom and Standard) and Text-to-speech (Custom and Standard) |
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|[Translator Text][tt-containers]| Translator Text |
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> [!IMPORTANT]
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> If a service or containerized offering is not listed, it's either not gated, or unavailable.
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## Next steps
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> [!div class="nextstepaction"]
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> [Sign up for gated services](https://forms.office.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbRyQZ7B8Cg2FEjpibPziwPcZUNlQ4SEVORFVLTjlBSzNLRlo0UzRRVVNPVy4u)
Copy file name to clipboardExpand all lines: articles/cognitive-services/containers/container-faq.md
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**Q: What is available?**
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**A:**[Container support in Azure Cognitive Services](../cognitive-services-container-support.md) allows developers to use the same intelligent APIs that are available in Azure, but with the [benefits](../cognitive-services-container-support.md#features-and-benefits) of containerization. Container support is currently available in preview for a subset of Azure Cognitive Services, including parts of:
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> [!div class="checklist"]
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> *[Anomaly Detector][ad-containers]
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> *[Computer Vision][cv-containers]
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> *[Face][fa-containers]
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> *[Form Recognizer][fr-containers]
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> *[Language Understanding (LUIS)][lu-containers]
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> *[Speech Service API][sp-containers]
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> *[Text Analytics][ta-containers]
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**A:** Azure Cognitive Services containers allow developers to use the same intelligent APIs that are available in Azure, but with the [benefits](../cognitive-services-container-support.md#features-and-benefits) of containerization. Some containers are available as a [gated preview](../cognitive-services-gating-process.md), which may require an application to access. Other containers are publicly available as an ungated preview, or are generally available. You can find a full list of containers and their availability in the [Container support in Azure Cognitive Services](../cognitive-services-container-support.md#container-availability-in-azure-cognitive-services) article.
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**Q: Is there any difference between the Cognitive Services cloud and the containers?**
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