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remove direct line speech docs
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articles/ai-services/.openpublishing.redirection.ai-services.json

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"redirect_url": "/windows/apps/design/input/speech-interactions",
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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/ai-services/speech-service/direct-line-speech.md",
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"redirect_url": "/azure/ai-services/speech-service/voice-assistants",
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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/ai-services/speech-service/quickstarts/voice-assistants.md",
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"redirect_url": "/azure/ai-services/speech-service/voice-assistants",
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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/ai-services/speech-service/tutorial-voice-enable-your-bot-speech-sdk.md",
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"redirect_url": "/azure/ai-services/speech-service/voice-assistants",
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"redirect_document_id": false
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},
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- name: Direct Line Speech
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items:
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- name: Direct Line Speech overview
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href: direct-line-speech.md
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- name: Custom voice assistant quickstart
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href: quickstarts/voice-assistants.md
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- name: Voice enable your bot
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href: tutorial-voice-enable-your-bot-speech-sdk.md
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{
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"source_path_from_root": "/articles/ai-services/qnamaker/how-to/migrate-to-openai.md",
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"redirect_url": "/azure/ai-services/qnamaker/overview/overview",

articles/ai-services/speech-service/direct-line-speech.md

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articles/ai-services/speech-service/includes/quickstarts/keyword-recognition/csharp.md

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> [!NOTE]
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> The example shown here uses local keyword recognition, since it does not require a `SpeechConfig`
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object for authentication context, and does not contact the back-end. However, you can run both keyword recognition and verification [utilizing a direct back-end connection](../../../tutorial-voice-enable-your-bot-speech-sdk.md#view-the-source-code-that-enables-keyword-detection).
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object for authentication context, and does not contact the back-end.
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### Continuous recognition
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articles/ai-services/speech-service/includes/quickstarts/voice-assistants/header.md

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ms.author: travisw
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---
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In this quickstart, you will use the [Speech SDK](~/articles/ai-services/speech-service/speech-sdk.md) to create a custom voice assistant application that connects to a bot that you have already authored and configured. If you need to create a bot, see [the related tutorial](~/articles/ai-services/speech-service/tutorial-voice-enable-your-bot-speech-sdk.md) for a more comprehensive guide.
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In this quickstart, you will use the [Speech SDK](~/articles/ai-services/speech-service/speech-sdk.md) to create a custom voice assistant application that connects to a bot that you have already authored and configured.
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After satisfying a few prerequisites, connecting your custom voice assistant takes only a few steps:
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> [!div class="checklist"]

articles/ai-services/speech-service/keyword-recognition-overview.md

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You don't need to explicitly specify any configuration parameters. All necessary information is automatically extracted from the on-device model generated by custom keyword.
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The sample and tutorials linked here show how to use the Speech SDK:
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* [Voice assistant samples on GitHub](https://github.com/Azure-Samples/Cognitive-Services-Voice-Assistant)
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* [Tutorial: Voice enable your assistant built using Azure AI Bot Service with the C# Speech SDK](./tutorial-voice-enable-your-bot-speech-sdk.md)
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## Speech SDK integration and scenarios
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The Speech SDK enables easy use of personalized on-device keyword recognition models generated with custom keyword and keyword verification. To ensure that your product needs can be met, the SDK supports the following two scenarios:
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| Scenario | Description | Samples |
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| -------- | ----------- | ------- |
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| End-to-end keyword recognition with speech to text | Best suited for products that use a customized on-device keyword model from custom keyword with keyword verification and speech to text. This scenario is the most common. | <ul><li>[Voice assistant sample code](https://github.com/Azure-Samples/Cognitive-Services-Voice-Assistant)</li><li>[Tutorial: Voice enable your assistant built using Azure AI Bot Service with the C# Speech SDK](./tutorial-voice-enable-your-bot-speech-sdk.md)</li></ul> |
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| Offline keyword recognition | Best suited for products without network connectivity that use a customized on-device keyword model from custom keyword. | <ul><li>[C# on Windows UWP sample](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/quickstart/csharp/uwp/keyword-recognizer)</li><li>[Java on Android sample](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/quickstart/java/android/keyword-recognizer)</li></ul>
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The offline keyword recognition scenario is best suited for products without network connectivity that use a customized on-device keyword model from custom keyword.
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- [C# on Windows UWP sample](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/quickstart/csharp/uwp/keyword-recognizer)
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- [Java on Android sample](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/quickstart/java/android/keyword-recognizer)
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## Next steps
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## Related content
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* [Read the quickstart to generate on-device keyword recognition models using custom keyword](custom-keyword-basics.md)
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* [Learn more about voice assistants](voice-assistants.md)

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