UFTBESD: University of Frontier Technology, Bangladesh-Bangla Emotional Speech Dataset

Md Rayhan Ali, Sadman Saeef, Mohammad Miftahul Islam Irfan Mohammad, Maliha Khan, Suchi Hasan, Sajib Das, Tanjim Taharat Aurpa, Sharad Hasan

UFTBESD (University of Frontier Technology, Bangladesh - Bangla Emotional Speech Dataset) is a Bangla-language speech emotion recognition dataset developed to capture realistic emotional speech under everyday acoustic conditions. The dataset consists of 1,400 audio recordings collected from 100 native Bangla speakers aged 15 to 38 years (mean age 22.6 years), with a balanced gender distribution (50 male and 50 female), recruited from all eight administrative divisions of Bangladesh. Each participant read two predefined Bangla sentences, with each sentence recorded once under each of seven target emotional states: angry, disgust, fear, happy, neutral, sad, and surprise. This yields 100 speakers x 2 sentences x 7 emotions = 1,400 audio clips. Every speaker contributes exactly 14 recordings, and every emotion category contains exactly 200 recordings (100 female, 100 male). All recordings were made using participants' own consumer smartphones in real indoor and outdoor environments (dormitory rooms, kitchens, courtyards, roadsides, etc.), without acoustic isolation or signal conditioning at any stage. A substantial portion of the corpus therefore contains natural background noise, device-specific microphone characteristics, and room reverberation, making it well suited to real-world speech emotion recognition research. Audio files are stored uncompressed as WAV (44.1 kHz, 16-bit PCM, mono), with durations ranging from 0.74 to 6.04 seconds (mean 2.68 s). This version corrects folder and file naming inconsistencies present in the previous release and adds a full metadata CSV file (one row per recording), covering speaker ID, pseudonym, age, gender, division, district, native dialect, education level, sentence text (Bangla and English), emotion label, recording environment, device brand/model, and audio properties. UFTBESD is intended to support the development and evaluation of Bangla speech emotion recognition systems and can be used with common machine learning and deep learning architectures such as CNN, LSTM, BiLSTM, and transformer-based models.