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

TL;DR

This paper introduces NISP, a comprehensive multilingual, multi-accent speech dataset with detailed speaker metadata, enabling advanced speaker profiling research across languages and physical traits.

Contribution

The creation of the NISP dataset with diverse languages, accents, and detailed speaker metadata is a novel resource for speaker profiling studies.

Findings

Baseline speaker profiling results on NISP dataset.

Demonstrated the dataset's potential for multi-lingual and multi-accent speaker analysis.

Potential applications in forensic and commercial speaker identification.

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.