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Copy file name to clipboardExpand all lines: articles/ai-services/speech-service/includes/quickstarts/openai-speech/csharp.md
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@@ -20,7 +20,7 @@ The Speech SDK is available as a [NuGet package](https://www.nuget.org/packages/
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### Set environment variables
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This example requires environment variables named `OPEN_AI_KEY`, `OPEN_AI_ENDPOINT`, `OPEN_AI_DEPLOYMENT_NAME`, `SPEECH_KEY`, and `SPEECH_REGION`.
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This example requires environment variables named `AZURE_OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_CHAT_DEPLOYMENT`, `SPEECH_KEY`, and `SPEECH_REGION`.
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```
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> [!IMPORTANT]
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> Make sure that you set the `OPEN_AI_KEY`, `OPEN_AI_ENDPOINT`, `OPEN_AI_DEPLOYMENT_NAME`, `SPEECH_KEY` and `SPEECH_REGION` [environment variables](#set-environment-variables) as described. If you don't set these variables, the sample will fail with an error message.
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> Make sure that you set the `AZURE_OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_CHAT_DEPLOYMENT`, `SPEECH_KEY` and `SPEECH_REGION` [environment variables](#set-environment-variables) as described. If you don't set these variables, the sample will fail with an error message.
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Speak into your microphone when prompted. The console output includes the prompt for you to begin speaking, then your request as text, and then the response from Azure OpenAI as text. The response from Azure OpenAI should be converted from text to speech and then output to the default speaker.
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- To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
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- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#input-text-streaming).
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- To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
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- To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal#deploy-a-model). The deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
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- Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.
Copy file name to clipboardExpand all lines: articles/ai-services/speech-service/includes/quickstarts/openai-speech/python.md
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### Set environment variables
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This example requires environment variables named `OPEN_AI_KEY`, `OPEN_AI_ENDPOINT`, `OPEN_AI_DEPLOYMENT_NAME`, `SPEECH_KEY`, and `SPEECH_REGION`.
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This example requires environment variables named `AZURE_OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_CHAT_DEPLOYMENT`, `SPEECH_KEY`, and `SPEECH_REGION`.
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```
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> [!IMPORTANT]
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> Make sure that you set the `OPEN_AI_KEY`, `OPEN_AI_ENDPOINT`, `OPEN_AI_DEPLOYMENT_NAME`, `SPEECH_KEY` and `SPEECH_REGION` environment variables as described [previously](#set-environment-variables). If you don't set these variables, the sample will fail with an error message.
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> Make sure that you set the `AZURE_OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_CHAT_DEPLOYMENT`, `SPEECH_KEY` and `SPEECH_REGION` environment variables as described [previously](#set-environment-variables). If you don't set these variables, the sample will fail with an error message.
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Speak into your microphone when prompted. The console output includes the prompt for you to begin speaking, then your request as text, and then the response from Azure OpenAI as text. The response from Azure OpenAI should be converted from text to speech and then output to the default speaker.
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- To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
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- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#input-text-streaming).
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- To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
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- To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource#deploy-a-model). Keep in mind that the deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
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- Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.
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