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--- |
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task_categories: |
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- text-classification |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset: Core Intents |
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The **Core Intents** dataset contains feedback-related utterances classified into seven key categories. This dataset is designed to help train voice assistants in handling fundamental types of feedback and adjusting their behavior accordingly. |
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## Labels |
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The dataset includes the following labels: |
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- **ask_clarify**: Requests for clarification, where the user seeks clearer explanations. |
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- **ask_confirmation**: Requests for confirmation, where the user asks to validate a previous command or statement. |
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- **ask_repeat**: Requests for repetition, where the user asks for something to be repeated. |
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- **negative_feedback**: Negative responses or corrections, indicating dissatisfaction or disagreement. |
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- **positive_feedback**: Positive responses, expressing satisfaction or agreement. |
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- **neutral_feedback**: Neutral responses, where the user shows indifference or general acceptance. |
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- **stop**: Commands indicating the user wants to halt an action or process. |
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## Examples |
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Sample utterances for each label: |
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- **ask_clarify**: |
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- "your response was not clear" |
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- "your words were not so clear to me" |
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- **ask_confirmation**: |
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- "can you check and confirm my last command please" |
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- "can you check and confirm it" |
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- **ask_repeat**: |
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- "would you try again please" |
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- "would you try what you said again" |
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- **negative_feedback**: |
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- "command wrong" |
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- "dammit, I did not say it" |
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- **positive_feedback**: |
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- "thanks, that's amazing" |
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- "that is excellent, much appreciated" |
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- **neutral_feedback**: |
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- "anything is fine" |
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- "any one would be good to me" |
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## Purpose |
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This dataset aims to cover core interactions a voice assistant should manage to provide responsive and adaptive behavior in real-time communication. It can be used in tasks such as: |
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- Intent classification |
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- Dialogue system training |
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- Feedback management in voice assistants |
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