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NISP: A Multi-lingual Multi-Accent Dataset for Speaker Profiling

Publication Type : Conference Paper

Publisher : IEEE

Source : Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2021, pp. 6953– 6957, 2021

Url : https://arxiv.org/abs/2007.06021

Campus : Amritapuri

Year : 2021

Abstract : Many commercial and forensic applications of speech demand the extraction of information about the speaker characteristics, which falls into the broad category of speaker profiling. The speaker characteristics needed for profiling include physical traits of the speaker like height, age, and gender of the speaker along with the native language of the speaker. Many of the datasets available have only partial information for speaker profiling. In this paper, we attempt to overcome this limitation by developing a new dataset which has speech data from five different Indian languages along with English. The metadata information for speaker profiling applications like linguistic information, regional information, and physical characteristics of a speaker are also collected. We call this dataset as NITK-IISc Multilingual Multi-accent Speaker Profiling (NISP) dataset. The description of the dataset, potential applications, and baseline results for speaker profiling on this dataset are provided in this paper.

Cite this Research Publication : Shareef Babu Kalluri, Deepu Vijayasenan, Sriram Ganapathy, Ragesh Rajan M, Prashant Krishnan, “NISP: A Multi-lingual Multi-Accent Dataset for Speaker Profiling”, in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2021, pp. 6953– 6957, 2021

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