SOTAVerified

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

Showing 13 of 3 papers

TitleStatusHype
CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AICode2
HADE: Hierarchical Affective Dialog Encoder for Personality Recognition in Conversation0
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in ConversationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BERT_ssenet^cAccuracy (%)67.25Unverified
2BERT^sAccuracy (%)67.23Unverified
3BERT^cAccuracy (%)66.32Unverified
4BERT_senet^cAccuracy (%)66.02Unverified