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Topic_Modeling
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LDA_Coherence, LDA_Perplexity
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Topic_Modeling
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# Topic_Modeling LDA_Coherence, LDA_Perplexity * [Measurement of the number of topics in children"s speech using LDA and Affinity propagation algorithm](http://www.dbpia.co.kr/Journal/articleDetail?nodeId=NODE09301947) (LDA와 선호도 전파 알고리즘을 이용한 아동 발화의 화제수 측정) * `Se-Eun Oh`, `Tak-Sung Heo`, `Yoonkyoung Lee`, `Yu-Seop Kim` ----------------------------------------------- ## Data * Children's speech data collected by the Department of Speech Pathology at Hallym University (Topic - School life, family life, other/friends) * 1st, 3rd, and 5th grade group data (Korean) * Data example | Turn | Utterance | Korean speech | English speech | | :------: | :---: | :-----: | :------: | | <학교> | | 검 학교생활은 어때? | Examiner: How is your school life? | 1 | 1 | 아 재미없어요. | Child: No fun. | | | 검 재미없구나. 그리고? | Examiner: That's not fun. And? | 2 | 2 | 아 점심 먹고 양치하고 | Child: Eat lunch and brush my teeth | | 3 | 아 근데 엄마 보고싶다. | Child: And, I miss my mom. ----------------------------------------------- ## Latent Dirichlet Allocation * LDA Topic Modeling * In LDA, the number of topics K is defined by the user, but the purpose of the study is to measure the number of topics using coherence and perplexity to measure the number of topics in speech. * Set K to 3-29 (K starts at 3 because the minimum number of topics in the data used in this study is 3). * Equation (1), standardization, is performed on the values of coherence and perplexity with topics from 3 to 29 through LDA. * *Standardization(x) = (x - mean(x)) / std(x)* (1) * In Equation (2), the highest value is defined as the prediction result. * *f(co,pe) = Standardization(co) - Standardization(pe)* (2) ----------------------------------------------- ## Experiment Result * Comparison of the number of topics in speech according to school age | Grade (age) | LDA | Speech pathology | | :-----: | :--: | :-----: | | 1 (8) | 19 | 19.5 | | 3 (10) | 4 | 17.2 | | 5 (12) | 4 | 12.5 | **The correlation coefficient between LDA and speech pathology - 0.7525** ----------------------------------------------- ## Conclusion * When looking at the correlation coefficient between LDA topic modeling and speech pathology, a high correlation coefficient was confirmed. * However, since the number of topics in the 3rd and 5th graders in LDA is the same, it is necessary to explore different topic modeling. * In future study, we plan to experiment with more sophisticated topic modeling, and through this, we will explore how to automate the number of topics.
