---
title: Dialogue Analysis
type: templates
category: Conversational AI
cat: conversational-ai
order: 815
meta_title: Dialogue Analysis Data Labeling Template
meta_description: Template for performing dialogue analysis for conversational AI use cases with Label Studio for your machine learning and data science projects.
---
If you want to evaluate and analyze the responses present in a dialogue that already happened, and optionally correct it, use this template.
Use this template to provide a section of dialogue and classify it. Annotators then provide the best response to the section of dialogue.
## Interactive Template Preview
## Labeling Configuration
```html
```
## About the labeling configuration
All labeling configurations must be wrapped in [View](/tags/view.html) tags.
Use the [HyperText](/tags/hypertext.html) object tag to display dialogue data, imported in Label Studio JSON format using a key of "dialogs":
```xml
```
You can add a [header](/tags/header.html) to provide instructions to the annotator:
```xml
```
Use the [Choices](/tags/choices.html) control tag in combination with the [Choice](/tags/choice.html) tag to have annotators classify the dialogue response. Use the arguments to control how the choices appear on the interface:
```xml
```
You can change the choice `value`s to provide different classification options.
Use the [TextArea](/tags/textarea.html) control tag to provide annotators with a free text box to supply their own response to the dialogue. Add the `editable=true` argument to allow them
to edit their answer, or `required=true` to force annotators to supply an alternate response:
```xml
```
## Related tags
- [HyperText](/tags/hypertext.html)
- [Choices](/tags/choices.html)
- [TextArea](/tags/textarea.html)