<p>HMM and RNN-LSTM based solutions are not considered highly accurate for SER.  I believe the ranking algorithm to date is one based on Deep Retinal
Convolution Neural Networks (DRCNNs).  See <a href="https://arxiv.org/ftp/arxiv/papers/1707/1707.09917.pdf" rel="nofollow noreferrer">Speech emotion recognition using Deep Retinal Convolution Neural Networks</a>, authored by Niu, Yafeng; Zou, Dongsheng; Niu, Yadong; He, Zhongshi; Tan, Hua and  published in July of 2017.  The authors achieved an average accuracy over 99% on the following databases: IEMOCAP, EMO-DB, and SAVEE.  </p>
HMM vs Deep Learning for Speech Emotion Recognition (SER)
<p>For building  Speech Emotion Detection and Recognition system, which approach would be better? Hidden Markov Model or Deep Learning (RNN-LSTM) approach? I have to build a SER system and I am confused between the two. If there are better models than these two, kindly tell.</p>