custom speech overview

Author: eric-urban

articles/ai-services/speech-service/custom-speech-overview.md

@@ -1,7 +1,7 @@
 ---
 title: Custom speech overview - Speech service
 titleSuffix: Azure AI services
-description: Custom speech is a set of online tools that allows you to evaluate and improve the speech to text accuracy for your applications, tools, and products.
+description: Custom speech is allows you to evaluate and improve the speech to text accuracy for your applications, tools, and products.
 author: eric-urban
 manager: nitinme
 ms.service: azure-ai-speech
@@ -30,13 +30,20 @@ With custom speech, you can upload your own data, test and train a custom model,
 Here's more information about the sequence of steps shown in the previous diagram:
 
 1. [Create a project](how-to-custom-speech-create-project.md) and choose a model. Use a <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesAIServices" title="Create an AI Services resource for Speech" target="_blank">Speech resource</a> that you create in the Azure portal. If you train a custom model with audio data, choose an AI Services resource for Speech region with dedicated hardware for training audio data. For more information, see footnotes in the [regions](regions.md#regions) table.
+
 1. [Upload test data](./how-to-custom-speech-upload-data.md). Upload test data to evaluate the speech to text offering for your applications, tools, and products.
-1. [Test recognition quality](how-to-custom-speech-inspect-data.md). Use the [Speech Studio](https://aka.ms/speechstudio/customspeech) to play back uploaded audio and inspect the speech recognition quality of your test data. 
-1. [Test model quantitatively](how-to-custom-speech-evaluate-data.md). Evaluate and improve the accuracy of the speech to text model. The Speech service provides a quantitative word error rate (WER), which you can use to determine if more training is required. 
+
 1. [Train a model](how-to-custom-speech-train-model.md). Provide written transcripts and related text, along with the corresponding audio data. Testing a model before and after training is optional but recommended.
+    
     > [!NOTE]
     > You pay for custom speech model usage and [endpoint hosting](how-to-custom-speech-deploy-model.md). You'll also be charged for custom speech model training if the base model was created on October 1, 2023 and later. You're not charged for training if the base model was created prior to October 2023. For more information, see [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) and the [Charge for adaptation section in the speech to text 3.2 migration guide](./migrate-v3-1-to-v3-2.md#charge-for-adaptation).
+
+1. [Test recognition quality](how-to-custom-speech-inspect-data.md). Use the [Speech Studio](https://aka.ms/speechstudio/customspeech) to play back uploaded audio and inspect the speech recognition quality of your test data. 
+
+1. [Test model quantitatively](how-to-custom-speech-evaluate-data.md). Evaluate and improve the accuracy of the speech to text model. The Speech service provides a quantitative word error rate (WER), which you can use to determine if more training is required. 
+
 1. [Deploy a model](how-to-custom-speech-deploy-model.md). Once you're satisfied with the test results, deploy the model to a custom endpoint. Except for [batch transcription](batch-transcription.md), you must deploy a custom endpoint to use a custom speech model.
+
     > [!TIP]
     > A hosted deployment endpoint isn't required to use custom speech with the [Batch transcription API](batch-transcription.md). You can conserve resources if the custom speech model is only used for batch transcription. For more information, see [Speech service pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/).