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Computer Science > Sound

arXiv:2105.08957 (cs)
[Submitted on 19 May 2021]

Title:SEMOUR: A Scripted Emotional Speech Repository for Urdu

Authors:Nimra Zaheer, Obaid Ullah Ahmad, Ammar Ahmed, Muhammad Shehryar Khan, Mudassir Shabbir
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Abstract:Designing reliable Speech Emotion Recognition systems is a complex task that inevitably requires sufficient data for training purposes. Such extensive datasets are currently available in only a few languages, including English, German, and Italian. In this paper, we present SEMOUR, the first scripted database of emotion-tagged speech in the Urdu language, to design an Urdu Speech Recognition System. Our gender-balanced dataset contains 15,040 unique instances recorded by eight professional actors eliciting a syntactically complex script. The dataset is phonetically balanced, and reliably exhibits a varied set of emotions as marked by the high agreement scores among human raters in experiments. We also provide various baseline speech emotion prediction scores on the database, which could be used for various applications like personalized robot assistants, diagnosis of psychological disorders, and getting feedback from a low-tech-enabled population, etc. On a random test sample, our model correctly predicts an emotion with a state-of-the-art 92% accuracy.
Comments: accepted in CHI 2021
Subjects: Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2105.08957 [cs.SD]
  (or arXiv:2105.08957v1 [cs.SD] for this version)
  https://doi.org/10.48550/arXiv.2105.08957
Related DOI: https://doi.org/10.1145/3411764.3445171

Submission history

From: Nimra Zaheer [view email]
[v1] Wed, 19 May 2021 07:15:03 UTC (1,471 KB)
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