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Emotion and Tone Adjusted Sentences
Social Media and Networking
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Free
About
This dataset provides a rich collection of English sentences, meticulously labelled with various emotions and expertly adapted into three distinct communication styles: Polite, Professional, and Casual. It serves as a valuable resource for Natural Language Processing (NLP) initiatives, particularly for tasks such as emotion identification, text style transformation, refining chatbot personalities, and generating multi-tone responses.
Columns
The dataset is structured with five key columns:
- Original: The initial, raw English sentence as spoken or written.
- Emotional label: The specific emotion conveyed by the original sentence, such as 'joy', 'sadness', 'anger', or 'love'.
- Polite: The original sentence rephrased to express the sentiment in a polite tone.
- Professional: The original sentence rephrased to express the sentiment in a professional tone.
- Casual: The original sentence rephrased to express the sentiment in a casual tone.
Distribution
The dataset is typically provided in a CSV file format, suitable for straightforward integration into various data processing workflows. The exact number of rows or records is not specified, however, it is structured to contain multiple examples of sentences for each emotion and tone transformation.
Usage
This dataset is ideally suited for a variety of applications, including:
- Developing and enhancing emotion detection models.
- Implementing style transfer mechanisms in text generation.
- Fine-tuning the personality and conversational style of chatbots.
- Creating systems capable of generating responses in multiple communication tones.
Coverage
The dataset's geographic scope is global, meaning the English sentences and their tone adjustments are applicable across diverse regions. Specific details regarding time range or demographic scope of the data content are not provided.
License
CC-BY-SA
Who Can Use It
This dataset is highly beneficial for:
- NLP Developers: For training and evaluating models related to text understanding and generation.
- AI/ML Researchers: Investigating new techniques in emotion analysis and stylistic text transformation.
- Chatbot Developers: Crafting more nuanced and context-aware conversational AI agents.
- Data Scientists: Analysing linguistic patterns and emotional expression in language.
Dataset Name Suggestions
- Emotion and Tone Adjusted Sentences
- Multitone Conversational English Data
- NLP Emotion-Style Dataset
- Chatbot Tone Training Sentences
Attributes
Original Data Source: Tone-Adjusted English Sentences for Chatbot & NLP
QUALITY