wxjiao/HiGRUs
Implementation of the paper "Hierarchical GRU for Utterance-level Emotion Recognition" in NAACL-2019.
This project helps researchers and practitioners in natural language processing analyze the emotional content of conversations. It takes dialogue transcripts as input and identifies the specific emotion expressed in each utterance. This is particularly useful for those working on improving customer service bots, mental health support systems, or social media monitoring tools.
No commits in the last 6 months.
Use this if you need to accurately detect and classify emotions within conversational text, especially when context and rare emotions are critical.
Not ideal if your primary goal is real-time, multimodal emotion detection involving audio or video, as this focuses on text-based analysis.
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Python
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Oct 06, 2020
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