We propose a model for carrying out deep learning based multimodal
sentiment analysis. The MOUD dataset is taken for experimentation
purposes. We developed two parallel text based and audio basedmodels and
further, fused these heterogeneous feature maps taken from intermediate
layers to complete thearchitecture. Performance measures–Accuracy,
precision, recall and F1-score–are observed to outperformthe existing models
S. P., Murthy, O. V. Ramana, and S. Veni, “Sentiment Analysis by Deep Learning Approaches”, TELKOMNIKA Telecommunication, Computing, Electronics and Control, vol. 18, 2 vol., 2020.