With automatic speaker verification (ASV) systems becoming increasingly popular, the development of robust countermeasures against spoofing is needed. Replay attacks pose a significant threat to the reliability of ASV systems because of the relative difficulty in detecting replayed speech and the ease with which such attacks can be mounted. In this paper, we propose an end-to-end deep learning framework for audio replay attack detection. Our proposed approach uses a novel visual attention mechanism on time-frequency representations of utterances based on group delay features, via deep residual learning (an adaptation of ResNet-18 architecture). Using a single model system, we achieve a perfect Equal Error Rate (EER) of 0% on both the development as well as the evaluation set of the ASVspoof 2017 dataset, against a previous best of 0.12% on the development set and 2.76% on the evaluation set reported in the literature. This highlights the efficacy of our feature representation and attention-based architecture in tackling the challenging task of audio replay attack detection.
This paper presents a novel approach towards Indic handwritten word recognition using zone-wise information. Because of complex nature due to compound characters, modifiers, overlapping and touching, etc., character segmentation and recognition is a tedious job in Indic scripts (e.g. Devanagari, Bangla, Gurumukhi, and other similar scripts). To avoid character segmentation in such scripts, HMMbased sequence modeling has been used earlier in holistic way. This paper proposes an efficient word recognition framework by segmenting the handwritten word images horizontally into three zones (upper, middle and lower) and recognize the corresponding zones. The main aim of this zone segmentation approach is to reduce the number of distinct component classes compared to the total number of classes in Indic scripts. As a result, use of this zone segmentation approach enhances the recognition performance of the system. The components in middle zone where characters are mostly touching are recognized using HMM. After the recognition of middle zone, HMM based Viterbi forced alignment is applied to mark the left and right boundaries of the characters. Next, the residue components, if any, in upper and lower zones in their respective boundary are combined to achieve the final word level recognition. Water reservoir feature has been integrated in this framework to improve the zone segmentation and character alignment defects while segmentation. A novel sliding window-based feature, called Pyramid Histogram of Oriented Gradient (PHOG) is proposed for middle zone recognition. PHOG features has been compared with other existing features and found robust in Indic script recognition. An exhaustive experiment is performed on two Indic scripts namely, Bangla and Devanagari for the performance evaluation. From the experiment, it has been noted that proposed zone-wise recognition improves accuracy with respect to the traditional way of Indic word recognition.Cite this as 1 @article{roy2016hmm,
An experiment was conducted to introduce the entomopathogen Beauveria bassiana (Balsamo) Vuillemin (Ascomycota: Hypocreales) as an endophyte in jute (Corchorus olitorius), a bast fibre crop through seed treatment. Colonization of root, leaf, stem, capsule, and seed were assessed through plating on selective medium and PCR based detection using B. bassiana specific SCAR markers. Endophytic colonization was detected in all the plants grown from treated seeds, but all the plant parts were not colonized. Colonization was detected in leaves, stems, and green capsules but not in roots and seeds. The endophytic colonization was influenced by both plant part and sampling period. Colonization was greater in leaves (55.87%) compared to stems (12.53%) and capsules (42.44%). The percent colonization was higher in case of 60 days old plants (43.34%) than in 30 days (23.89%) and 120 days (35.39%) old plants. As B. bassiana has already been reported to be pathogenic on jute pests, namely semilooper (Anomis sabulifera) and bihar hairy caterpillar (Spilosoma obliqua), its season long endophytic colonization within jute plant suggests a novel approach of biological control of these pests through seed treatment with the entomopathogen.
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