BanglaSER: A Bangla speech emotion recognition dataset

BanglaSER is a Bangla language-based speech emotion recognition dataset. It consists of speech-audio data of 34 participating speakers from diverse age groups between 19 and 47 years, with a balanced 17 male and 17 female nonprofessional participating actors. This dataset contains 1467 Bangla speech-audio recordings of five rudimentary human emotional states, namely angry, happy, neutral, sad, and surprise. Three trials are conducted for each emotional state. Hence, the total number of recordings involves 3 statements × 3 repetitions × 4 emotional states (angry, happy, sad, and surprise) × 34 participating speakers = 1224 recordings + 3 statements × 3 repetitions × 1 emotional state (neutral) × 27 participating speakers = 243 recordings, making the total number of recordings of 1467. BanglaSER dataset is collected by recording through smartphones, and laptops, having a balanced number of recordings in each category with evenly distributed participating male and female actors, preserves the real-life environment, and would serve as an essential training dataset for the speech emotion recognition model in terms of generalization. BanglaSER is compatible with various deep learning architectures such as CNN, LSTM, BiLSTM etc.