음성 데이터를 4초 길이로 자른 후, MFCC를 사용해 특징 벡터를 추출합니다. 추출한 특징 벡터는 감정 별로 값의 범위가 다양하기 때문에 Scaler를 사용해 표준화시킵니다. Scaler는 MinMax Scaler를 사용했습니다. 이후 SVM 모델을 학습시킵니다.
완성된 모델의 정확도는 약 85%이며, 각 감정에 대한 예측 결과는 아래와 같습니다.
⚙ 감정 인식 모델 개발 ⚙
Goal: 정확도 80% 이상
4.30 미팅 후 할일 추가
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