Merge pull request #284940 from sally-baolian/patch-288

Update how-to-lower-speech-synthesis-latency.md

Author: prmerger-automator[bot]

articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md

@@ -318,16 +318,18 @@ For Linux and Windows, `GStreamer` is required to enable this feature.
 Refer [this instruction](how-to-use-codec-compressed-audio-input-streams.md) to install and configure `GStreamer` for Speech SDK.
 For Android, iOS and macOS, no extra configuration is needed starting version 1.20.
 
-## Text streaming
+## Input text streaming
 
 Text streaming allows real-time text processing for rapid audio generation. It's perfect for dynamic text vocalization, such as reading outputs from AI models like GPT in real-time. This feature minimizes latency and improves the fluidity and responsiveness of audio outputs, making it ideal for interactive applications, live events, and responsive AI-driven dialogues.
 
 ### How to use text streaming
 
-To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+Currently, only C#, C++ and Python are supported in the SDK. Support for Java and Objective-C is planned for future releases.
 
 ::: zone pivot="programming-language-csharp"
 
+To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+
 See the sample code for setting the endpoint:
 
 ```csharp
@@ -360,6 +362,8 @@ For detailed implementation, see the [sample code on GitHub](https://github.com/
 
 ::: zone pivot="programming-language-python"
 
+To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+
 See the sample code for setting the endpoint:
 
 ```python
@@ -385,6 +389,33 @@ For detailed implementation, see the [sample code on GitHub](https://github.com/
 
 ::: zone-end
 
+::: zone pivot="programming-language-cpp"
+
+The C++ sample code isn't available now. For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
+::: zone pivot="programming-language-java"
+
+For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
+::: zone pivot="programming-language-objectivec"
+
+For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
 ## Others tips
 
 ### Cache CRL files

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

@@ -230,7 +230,7 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - 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.
-- 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#text-streaming).
+- 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).
 - 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.
 - 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/).
 - 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.

articles/ai-services/speech-service/includes/quickstarts/openai-speech/python.md

@@ -177,7 +177,7 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - 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.
-- 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#text-streaming).
+- 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).
 - 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.
 - 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/).
 - 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.