Abstract
Lambani is an under-resourced Indo-Aryan language spoken by a nomadic tribe known as the ‘Banjara people’ across central and southern India. Due to its contact with several major languages of India, Lambani has been influenced both linguistically as well as culturally. One of the major influences has been observed in its phonemic inventory. This paper is a preliminary investigation into the acoustic characteristics of vowels of the language. The paper analyses spectral and temporal features of six Lambani vowels, viz. spoken in the Bagalkot district of Karnataka. The results obtained throw light on the distinctiveness of this variety. The paper then uses spectral and temporal features to explore both machine learning and deep learning approaches to classify Lambani vowel perceptual space. Results show that Fully Connected Dense Layer achieves better accuracy in classifying Lambani vowels.
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Acknowledgment
This paper is part of an ongoing project ‘Speech-to-speech translation of low-resource tribal languages’ supported by the Ministry of Electronics and Information Technology (MeitY), India. The authors thank Prof. K. Samudravijaya for his suggestions on vowel classification.
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Dihingia, L., Bannulmath, P., Chowdhury, A.R., Prasanna, S., Deepak, K., Sheikh, T. (2023). Preliminary Analysis of Lambani Vowels and Vowel Classification Using Acoustic Features. In: Karpov, A., Samudravijaya, K., Deepak, K.T., Hegde, R.M., Agrawal, S.S., Prasanna, S.R.M. (eds) Speech and Computer. SPECOM 2023. Lecture Notes in Computer Science(), vol 14339. Springer, Cham. https://doi.org/10.1007/978-3-031-48312-7_16
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