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- # Blended Skill Talk
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  ## Dataset Summary
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- This dataset contains conversations between two personas with additional context, previous utterances, free messages, guided messages, suggestions and guided chosen suggestions, allowing for the creation of natural multi-modal conversations with personality, empathy and knowledge. The conversations are designed to measure a full range of technical competencies such as dialog flow management (including response times), topic control and coherence of conversation. It also provides a basis for exploring the impact of different conversational styles on user engagement. Additionally, the task is useful in validating distributed dialogue systems across various modalities while revealing potential biases present in different contexts. Finally, it enables benchmarking against data sets in similar areas towards development of an automatic evaluation system to effectively grade tactical skill talk performance over time.
 
 
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  ## Data Structure
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  ### Fields
 
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  | Field | Description |
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  |:------|:-------------|
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  | personas | List of personas participating in the conversation. |
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  ### Splits
 
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  | Split | Examples | Size (bytes) | Description |
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  |:------|----------:|-------------:|:-------------|
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- | Train | 4,096 | 9,201,244 | Used for model training |
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- | Validation | 723 | 1,629,426 | Used for validation and tuning |
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- **Total dataset size:** 10,830,670 bytes
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- **Total number of dialogues:** 4,819
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+ # Blended Skill Talk - ShareGPT Processed
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  ## Dataset Summary
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+ This dataset contains conversations between two personas with additional context, previous utterances, free messages, guided messages, suggestions, and guided chosen suggestions, allowing for the creation of natural multi-modal conversations with personality, empathy, and knowledge.
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+ The conversations are designed to measure a full range of technical competencies such as dialogue flow management (including response times), topic control, and coherence of conversation. It also provides a basis for exploring the impact of different conversational styles on user engagement. Additionally, the dataset is useful for validating distributed dialogue systems across various modalities while revealing potential biases present in different contexts. Finally, it enables benchmarking against similar datasets toward the development of an automatic evaluation system for assessing tactical skill talk performance over time.
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  ## Data Structure
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  ### Fields
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  | Field | Description |
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  |:------|:-------------|
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  | personas | List of personas participating in the conversation. |
 
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  ### Splits
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  | Split | Examples | Size (bytes) | Description |
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  |:------|----------:|-------------:|:-------------|
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+ | Train | 4096 | 9201244 | Used for model training |
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+ | Validation | 723 | 1629426 | Used for validation and tuning |
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+ **Total dataset size:** 10830670 bytes
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+ **Total number of dialogues:** 4819
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