Personality Recognition in Conversation
Given a speaker's conversation with others, it is required to recognize the speaker's personality traits through the conversation record, which includes two scenarios, (1) $1-1$ conversations: the robot recognizes the personality traits of the speaker through the conversation between them (e.g., psychological counseling), (2) $1-N$ conversations : the robot listens to the speaker's conversations with other $N$ people and then recognizes the speaker's personality traits (e.g., group chatbot, home service robot). Since $1-N$ includes the case of $1-1$, we only discusses PRC in $1-N$ conversations. The task of PRC in $1-N$ conversations can be formulated as:
$Per_i = argmax_{Per'i}P(Per'i | C{i,j}, \cdots, C{i,N})$
where $Per_i=[Neu, Ext, Ope, Agr, Con]$ is a 5-dimensional vector representing Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness. $C_{i,j}$ is the conversations between $Speaker_i$ and $Speaker_j$ ($1 \leq j \leq N$).
Papers
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Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BERT_ssenet^c | Accuracy (%) | 67.25 | — | Unverified |
| 2 | BERT^s | Accuracy (%) | 67.23 | — | Unverified |
| 3 | BERT^c | Accuracy (%) | 66.32 | — | Unverified |
| 4 | BERT_senet^c | Accuracy (%) | 66.02 | — | Unverified |