Browsing by Author "Ahsan, H."

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Multi-label annotation of music
(2015) Ahsan, H.; Kumar, V.; Jawahar, C.V.
Automatic annotation of an audio or a music piece with multiple labels helps in understanding the composition of a music. Such meta-level information can be very useful in applications such as music transcription, retrieval, organization and personalization. In this work, we formulate the problem of annotation as multi-label classification which is considerably different from that of a popular single (binary or multi-class) label classification. We employ both the nearest neighbour and max-margin (SVM) formulations for the automatic annotation. We consider K-NN and SVM that are adapted for multi-label classification using one-vs-rest strategy and a direct multi-label classification formulation using ML-KNN and M3L. In the case of music, often the signatures of the labels (e.g. instruments and vocal signatures) are fused in the features. We therefore propose a simple feature augmentation technique based on non-negative matrix factorization (NMF) with an intuition to decompose a music piece into its constituent components. We conducted our experiments on two data sets - Indian classical instruments dataset and Emotions dataset [1], and validate the methods. � 2015 IEEE.
Multi-label annotation of music
(Institute of Electrical and Electronics Engineers Inc., 2015) Ahsan, H.; Kumar, V.; Jawahar, C.V.
Automatic annotation of an audio or a music piece with multiple labels helps in understanding the composition of a music. Such meta-level information can be very useful in applications such as music transcription, retrieval, organization and personalization. In this work, we formulate the problem of annotation as multi-label classification which is considerably different from that of a popular single (binary or multi-class) label classification. We employ both the nearest neighbour and max-margin (SVM) formulations for the automatic annotation. We consider K-NN and SVM that are adapted for multi-label classification using one-vs-rest strategy and a direct multi-label classification formulation using ML-KNN and M3L. In the case of music, often the signatures of the labels (e.g. instruments and vocal signatures) are fused in the features. We therefore propose a simple feature augmentation technique based on non-negative matrix factorization (NMF) with an intuition to decompose a music piece into its constituent components. We conducted our experiments on two data sets - Indian classical instruments dataset and Emotions dataset [1], and validate the methods. Â© 2015 IEEE.
Vision based laser controlled keyboard system for the disabled
(2014) Ahsan, H.; Prabhu, A.; Deeksha, S.D.; Domanal, S.G.; Ashwin, T.S.; Ram Mohana Reddy, Guddeti
In this paper, we have proposed a novel design for a vision based unistroke keyboard system for the disabled. The keyboard layout considers the commonly used character patterns, which makes it convenient for the user to type. In addition to this, Shift functionality is provided to accommodate a larger set of characters. A webcam is positioned so as to monitor the keyboard and the characters are identified based on the laser pointer which the user can control by minor head movements. Experimental results demonstrate that the design achieves very promising results, thus establishing a baseline for such models in this domain. Copyright 2014 ACM.
Vision based laser controlled keyboard system for the disabled
(Association for Computing Machinery, 2014) Ahsan, H.; Prabhu, A.; Deeksha, S.D.; Domanal, S.G.; Ashwin, T.S.; Guddeti, G.R.M.
In this paper, we have proposed a novel design for a vision based unistroke keyboard system for the disabled. The keyboard layout considers the commonly used character patterns, which makes it convenient for the user to type. In addition to this, Shift functionality is provided to accommodate a larger set of characters. A webcam is positioned so as to monitor the keyboard and the characters are identified based on the laser pointer which the user can control by minor head movements. Experimental results demonstrate that the design achieves very promising results, thus establishing a baseline for such models in this domain. Â© 2014 ACM.