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

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 o...

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Bibliographic Details
Published inICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 6953 - 6957
Main Authors Kalluri, Shareef Babu, Vijayasenan, Deepu, Ganapathy, Sriram, M, Ragesh Rajan, Krishnan, Prashant
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.06.2021
Subjects
Forensics
Frequency measurement
Harmonic analysis
Linguistics
NISP dataset
Physical parameters
Predictive models
Signal processing
Speaker profiling
Training
Voice forensics
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Summary: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 meta-data 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.
ISSN:2379-190X
DOI:10.1109/ICASSP39728.2021.9414349