Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Vijayasenan, D.Subject: search.filters.subject.Physical parameters

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    Estimating multiple physical parameters from speech data
    (IEEE Computer Society help@computer.org, 2016) Kalluri, S.B.; Vijayakumar, A.; Vijayasenan, D.; Singh, R.
    In this work, we explore prediction of different physical parameters from speech data. We aim to predict shoulder size and waist size of people from speech data in addition to the conventional height and weight parameters. A data-set with this information is created from 207 volunteers. A bag of words representation based on log magnitude spectrum is used as features. A support vector regression predicts the physical parameters from the bag of the words representation. The system is able to achieve a root mean square error of 6.6 cm for height estimation, 2.6cm for shoulder size, 7.1cm for waist size and 8.9 kg for weight estimation. The results of height estimation is on par with state of the art results. © 2016 IEEE.
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    Robust features for automatic estimation of physical parameters from speech
    (Institute of Electrical and Electronics Engineers Inc., 2017) Kalluri, K.S.; Vijayasenan, D.
    Estimating speaker's physical parameters like height, weight and shoulder size can assist in voice forensics by providing additional knowledge about the speaker. In this work, statistics of the components of background GMM are employed as features in estimating the physical parameters. These features improved the performance of height and shoulder size estimation as compared to our earlier attempt based on a Bag of Word representation. The robustness of the features is validated using two different training subsets containing different languages. © 2017 IEEE.
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    Nisp: A multi-lingual multi-accent dataset for speaker profiling
    (Institute of Electrical and Electronics Engineers Inc., 2021) Kalluri, S.B.; Vijayasenan, D.; Ganapathy, S.; Rajan, M.; Krishnan, P.
    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. © 2021 IEEE.