BANSpEmo: A Bangla Emotional Speech Recognition Dataset

Md Gulzar Hussain, Mahmuda Rahman, Babe Sultana, Ye Shiren
12/21/2023
cs.HCcs.LGcs.SD

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Abstract

In the field of audio and speech analysis, the ability to identify emotions from acoustic signals is essential. Human-computer interaction (HCI) and behavioural analysis are only a few of the many areas where the capacity to distinguish emotions from speech signals has an extensive range of applications. Here, we are introducing BanSpEmo, a corpus of emotional speech that only consists of audio recordings and has been created specifically for the Bangla language. This corpus contains 792 audio recordings over a duration of more than 1 hour and 23 minutes. 22 native speakers took part in the recording of two sets of sentences that represent the six desired emotions. The data set consists of 12 Bangla sentences which are uttered in 6 emotions as Disgust, Happy, Sad, Surprised, Anger, and Fear. This corpus is not also gender balanced. Ten individuals who either have experience in related field or have acting experience took part in the assessment of this corpus. It has a balanced number of audio recordings in each emotion class. BanSpEmo can be considered as a useful resource to promote emotion and speech recognition research and related applications in the Bangla language. The dataset can be found here: https://data.mendeley.com/datasets/rdwn4bs5ky and might be employed for academic research.

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@article{hussain2023banspemo,
  title  = {BANSpEmo: A Bangla Emotional Speech Recognition Dataset},
  author = {Md Gulzar Hussain and Mahmuda Rahman and Babe Sultana and Ye Shiren},
  year   = {2023},
  eprint = {2312.14020},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.14020v1}
}

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