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.openpublishing.redirection.container-registry.json

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},
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{
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"source_path": "articles/container-registry/container-registry-diagnostics-audit-logs.md",
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"redirect_url": "/azure/container-registry/monitor-service"
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"redirect_url": "/azure/container-registry/monitor-container-registry"
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},
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{
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"source_path_from_root": "/articles/container-registry/container-registry-managed-get-started-azure-cli.md",
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"source_path_from_root": "/articles/container-registry/github-action-scan.md",
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"redirect_url": "/azure/developer/github/",
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"redirect_document_id": false
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},
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{
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"source_path": "articles/container-registry/monitor-service.md",
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"redirect_url": "/azure/container-registry/monitor-container-registry",
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"redirect_document_id": true
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},
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{
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"source_path": "articles/container-registry/monitor-service-reference.md",
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"redirect_url": "/azure/container-registry/monitor-container-registry-reference",
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"redirect_document_id": true
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}
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]
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}

.openpublishing.redirection.json

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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/backup/azure-backup-move-vaults-across-regions.md",
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"redirect_url": "/azure/operational-excellence/relocation-backup",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/cosmos-db/how-to-move-regions.md",
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"redirect_url": "/azure/operational-excellence/relocation-cosmos-db",
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"redirect_document_id": false
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"source_path_from_root": "/articles/virtual-network/ip-services/create-vm-dual-stack-ipv6-powershell.md",
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"redirect_url": "/azure/virtual-network/ip-services/create-vm-dual-stack-ipv6-portal",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/virtual-network/ip-services/routing-preference-powershell.md",
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"redirect_url": "/azure/virtual-network/ip-services/routing-preference-portal",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/virtual-network/ip-services/routing-preference-cli.md",
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"redirect_url": "/azure/virtual-network/ip-services/routing-preference-portal",
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"redirect_document_id": false
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}
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]

articles/active-directory-b2c/custom-email-sendgrid.md

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<LocalizedString ElementType="DisplayControl" ElementId="emailVerificationControl" StringId="but_send_new_code">Send new code</LocalizedString>
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<LocalizedString ElementType="DisplayControl" ElementId="emailVerificationControl" StringId="but_change_claims">Change e-mail</LocalizedString>
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<!-- Claims-->
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<LocalizedString ElementType="ClaimType" ElementId="emailVerificationCode" StringId="DisplayName">Verification Code</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="emailVerificationCode" StringId="UserHelpText">Verification code received in the email.</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="emailVerificationCode" StringId="AdminHelpText">Verification code received in the email.</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="VerificationCode" StringId="DisplayName">Verification Code</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="VerificationCode" StringId="UserHelpText">Verification code received in the email.</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="VerificationCode" StringId="AdminHelpText">Verification code received in the email.</LocalizedString>
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<LocalizedString ElementType="ClaimType" ElementId="email" StringId="DisplayName">Email</LocalizedString>
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<!-- Email validation error messages-->
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<LocalizedString ElementType="ErrorMessage" StringId="UserMessageIfSessionDoesNotExist">You have exceeded the maximum time allowed.</LocalizedString>

articles/ai-services/openai/concepts/use-your-data.md

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The estimates also depend on the nature of the documents and questions being asked. For example, if the questions are open-ended, the responses are likely to be longer. Similarly, a longer system message would contribute to a longer prompt that consumes more tokens, and if the conversation history is long, the prompt will be longer.
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| Model | Max tokens for system message | Max tokens for model response |
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|--|--|--|
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| GPT-35-0301 | 400 | 1500 |
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| GPT-35-0613-16K | 1000 | 3200 |
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| GPT-4-0613-8K | 400 | 1500 |
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| GPT-4-0613-32K | 2000 | 6400 |
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The table above shows the maximum number of tokens that can be used for the [system message](#system-message) and the model response. Additionally, the following also consume tokens:
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| Model | Max tokens for system message |
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|--|--|
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| GPT-35-0301 | 400 |
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| GPT-35-0613-16K | 1000 |
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| GPT-4-0613-8K | 400 |
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| GPT-4-0613-32K | 2000 |
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| GPT-35-turbo-0125 | 2000 |
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| GPT-4-turbo-0409 | 4000 |
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| GPT-4o | 4000 |
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| GPT-4o-mini | 4000 |
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The table above shows the maximum number of tokens that can be used for the [system message](#system-message). To see the maximum tokens for the model response, see the [models article](./models.md#gpt-4-and-gpt-4-turbo-models). Additionally, the following also consume tokens:
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articles/ai-services/openai/how-to/deployment-types.md

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> [!IMPORTANT]
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> Data might be processed outside of the resource's Azure geography, but data storage remains in its Azure geography. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
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Global deployments are available in the same Azure OpenAI resources as non-global offers but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request. Global standard will provide the highest default quota for new models and eliminates the need to load balance across multiple resources.
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Global deployments are available in the same Azure OpenAI resources as non-global deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request. Global standard provides the highest default quota and eliminates the need to load balance across multiple resources.
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The deployment type is optimized for low to medium volume workloads with high burstiness. Customers with high consistent volume may experience greater latency variability. The threshold is set per model. See the [quotas page to learn more](./quota.md).
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For customers that require the lower latency variance at large workload usage, we recommend purchasing provisioned throughput.
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Customers with high consistent volume may experience greater latency variability. The threshold is set per model. See the [quotas page to learn more](./quota.md). For applications that require the lower latency variance at large workload usage, we recommend purchasing provisioned throughput.
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### How to disable access to global deployments in your subscription
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articles/ai-services/openai/quotas-limits.md

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|Tier| Quota Limit in tokens per minute (TPM) | Requests per minute |
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|---|:---:|:---:|
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|Enterprise agreement | 30 M | 60 K |
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|Enterprise agreement | 30 M | 180 K |
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|Default | 450 K | 2.7 K |
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M = million | K = thousand

articles/ai-services/speech-service/text-to-speech-avatar/avatar-gestures-with-ssml.md

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author: eric-urban
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---
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# Customize text to speech avatar gestures with SSML (preview)
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[!INCLUDE [Text to speech avatar preview](../includes/text-to-speech-avatar-preview.md)]
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# Customize text to speech avatar gestures with SSML
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The [Speech Synthesis Markup Language (SSML)](../speech-synthesis-markup-structure.md) with input text determines the structure, content, and other characteristics of the text to speech output. Most SSML tags can also work in text to speech avatar. Furthermore, text to speech avatar batch mode provides avatar gestures insertion ability by using the SSML bookmark element with the format `<bookmark mark='gesture.*'/>`.
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articles/ai-services/speech-service/text-to-speech-avatar/batch-synthesis-avatar-properties.md

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---
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# Batch synthesis properties for text to speech avatar (preview)
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[!INCLUDE [Text to speech avatar preview](../includes/text-to-speech-avatar-preview.md)]
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# Batch synthesis properties for text to speech avatar
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Batch synthesis properties can be grouped as: avatar related properties, batch job related properties, and text to speech related properties, which are described in the following tables.
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articles/ai-services/speech-service/text-to-speech-avatar/batch-synthesis-avatar.md

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---
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# How to use batch synthesis for text to speech avatar (preview)
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# How to use batch synthesis for text to speech avatar
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[!INCLUDE [Text to speech avatar preview](../includes/text-to-speech-avatar-preview.md)]
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The batch synthesis API for text to speech avatar (preview) allows for the asynchronous synthesis of text into a talking avatar as a video file. Publishers and video content platforms can utilize this API to create avatar video content in a batch. That approach can be suitable for various use cases such as training materials, presentations, or advertisements.
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The batch synthesis API for text to speech avatar allows for the asynchronous synthesis of text into a talking avatar as a video file. Publishers and video content platforms can utilize this API to create avatar video content in a batch. That approach can be suitable for various use cases such as training materials, presentations, or advertisements.
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The synthetic avatar video will be generated asynchronously after the system receives text input. The generated video output can be downloaded in batch mode synthesis. You submit text for synthesis, poll for the synthesis status, and download the video output when the status indicates success. The text input formats must be plain text or Speech Synthesis Markup Language (SSML) text.
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| Operation | Method | REST API call |
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|----------------------|---------|---------------------------------------------------|
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| [Create batch synthesis](#create-a-batch-synthesis-request) | PUT | avatar/batchsyntheses/{SynthesisId}?api-version=2024-04-15-preview |
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| [Get batch synthesis](#get-batch-synthesis) | GET | avatar/batchsyntheses/{SynthesisId}?api-version=2024-04-15-preview |
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| [List batch synthesis](#list-batch-synthesis) | GET | avatar/batchsyntheses/?api-version=2024-04-15-preview |
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| [Delete batch synthesis](#delete-batch-synthesis) | DELETE | avatar/batchsyntheses/{SynthesisId}?api-version=2024-04-15-preview |
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| [Create batch synthesis](#create-a-batch-synthesis-request) | PUT | avatar/batchsyntheses/{SynthesisId}?api-version=2024-08-01 |
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| [Get batch synthesis](#get-batch-synthesis) | GET | avatar/batchsyntheses/{SynthesisId}?api-version=2024-08-01 |
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| [List batch synthesis](#list-batch-synthesis) | GET | avatar/batchsyntheses/?api-version=2024-08-01 |
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| [Delete batch synthesis](#delete-batch-synthesis) | DELETE | avatar/batchsyntheses/{SynthesisId}?api-version=2024-08-01 |
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You can refer to the code samples on [GitHub](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/batch-avatar).
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"talkingAvatarCharacter": "lisa",
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"talkingAvatarStyle": "graceful-sitting"
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}' "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/my-job-01?api-version=2024-04-15-preview"
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}' "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/my-job-01?api-version=2024-08-01"
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You should receive a response body in the following format:
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Replace `YourSynthesisId` with your batch synthesis ID, `YourSpeechKey` with your Speech resource key, and `YourSpeechRegion` with your Speech resource region.
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```azurecli-interactive
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curl -v -X GET "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/YourSynthesisId?api-version=2024-04-15-preview" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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curl -v -X GET "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/YourSynthesisId?api-version=2024-08-01" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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You should receive a response body in the following format:
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Replace `YourSpeechKey` with your Speech resource key and `YourSpeechRegion` with your Speech resource region. Optionally, you can set the `skip` and `top` (page size) query parameters in the URL. The default value for `skip` is 0, and the default value for `maxpagesize` is 100.
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```azurecli-interactive
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curl -v -X GET "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses?skip=0&maxpagesize=2&api-version=2024-04-15-preview" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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curl -v -X GET "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses?skip=0&maxpagesize=2&api-version=2024-08-01" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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You receive a response body in the following format:
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"nextLink": "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/?api-version=2024-04-15-preview&skip=2&maxpagesize=2"
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"nextLink": "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/?api-version=2024-08-01&skip=2&maxpagesize=2"
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To delete a batch synthesis job, make an HTTP DELETE request using the following URI format. Replace `YourSynthesisId` with your batch synthesis ID, `YourSpeechKey` with your Speech resource key, and `YourSpeechRegion` with your Speech resource region.
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```azurecli-interactive
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curl -v -X DELETE "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/YourSynthesisId?api-version=2024-04-15-preview" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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curl -v -X DELETE "https://YourSpeechRegion.api.cognitive.microsoft.com/avatar/batchsyntheses/YourSynthesisId?api-version=2024-08-01" -H "Ocp-Apim-Subscription-Key: YourSpeechKey"
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The response headers include `HTTP/1.1 204 No Content` if the delete request was successful.

articles/ai-services/speech-service/text-to-speech-avatar/custom-avatar-create.md

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# How to create a custom text to speech avatar (preview)
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[!INCLUDE [Text to speech avatar preview](../includes/text-to-speech-avatar-preview.md)]
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# How to create a custom text to speech avatar
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Getting started with a custom text to speech avatar is a straightforward process. All it takes are a few of video files. If you'd like to train a [custom neural voice](../custom-neural-voice.md) for the same actor, you can do so separately.
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