Abstract
This paper presents an automatic dialect identification in Ao using modulation-based approach. Ao is a low-resource, Tibeto-Burman tonal language spoken in Nagaland, a North-East state of India. This work aims to investigate dialect-specific characteristics to build a more robust DID system for classifying the three Ao dialects. In this direction, modulation-based representation is explored. Considering Ao is a tone language, the experiments were evaluated for 3 sec segment duration in order to capture the temporal information of the modulation spectrogram. In addition, the log Mel spectrogram is used as the feature for the baseline DID system. The proposed modulation spectrogram shows a significant performance of \(\approx 8\%\) improvement in accuracy over the baseline Ao DID system. Hence, the result indicates the effectiveness of modulation-based representation in automatically identifying the three dialects of Ao.
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Tzudir, M., Sadashiv T.N., R., Agarwal, A., Prasanna, S.R.M. (2023). Dialect Identification in Ao Using Modulation-Based Representation. 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_43
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