Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084860
R. Sriranjani, B. MuraliKarthick, S. Umesh
In this paper, we investigate the performance of deep neural network (DNN) and Subspace Gaussian mixture model (SGMM) in low-resource condition. Even though DNN outperforms SGMM and continuous density hidden Markov models (CDHMM) for high-resource data, it degrades in performance while modeling low-resource data. Our experimental results show that SGMM outperforms DNN for limited transcribed data. To resolve this problem in DNN, we propose to train DNN containing bottleneck layer in two stages: First stage involves extraction of bottleneck features. In second stage, the extracted bottleneck features from first stage are used to train DNN having bottleneck layer. All our experiments are performed using two Indian languages (Tamil & Hindi) in Mandi database. Our proposed method shows improved performance when compared to baseline SGMM and DNN models for limited training data.
{"title":"Investigation of different acoustic modeling techniques for low resource Indian language data","authors":"R. Sriranjani, B. MuraliKarthick, S. Umesh","doi":"10.1109/NCC.2015.7084860","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084860","url":null,"abstract":"In this paper, we investigate the performance of deep neural network (DNN) and Subspace Gaussian mixture model (SGMM) in low-resource condition. Even though DNN outperforms SGMM and continuous density hidden Markov models (CDHMM) for high-resource data, it degrades in performance while modeling low-resource data. Our experimental results show that SGMM outperforms DNN for limited transcribed data. To resolve this problem in DNN, we propose to train DNN containing bottleneck layer in two stages: First stage involves extraction of bottleneck features. In second stage, the extracted bottleneck features from first stage are used to train DNN having bottleneck layer. All our experiments are performed using two Indian languages (Tamil & Hindi) in Mandi database. Our proposed method shows improved performance when compared to baseline SGMM and DNN models for limited training data.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084889
Madhusmita Mohanty, U. Satija, Barathram Ramkumar, M. Manikandan
In recent years, automatic signal detection and modulation classification play a vital role in the field of cognitive radio applications. The majority of the existing signals detection and classification methods assume that the received signal is contaminated by additive white Gaussian noise. Under impulsive noise condition, the performance of the traditional modulation classification methods may be degraded. Therefore, in this paper, we investigate the application of sparse signal decomposition using an overcomplete dictionary for detection and classification of digital modulation signals. The overcomplete hybrid dictionary consists of impulse waveform and sine and cosine waveform for effectively capturing morphological components of the impulse noise and deterministic modulated signals. The proposed modulation classification method includes the following steps: sparse signal decomposition (SSD) on hybrid dictionaries, modulated signal extraction, matched filtering, and maximum likelihood (ML) classification. The performance of the direct ML and SSD-based ML classification methods are tested and validated using different modulation techniques under different Gaussian and impulse noise conditions. The proposed system achieves a classification accuracy of 89 percent at 0 dB SNR and hence outperforms the direct ML method.
{"title":"Digital modulation classification under non-Gaussian noise using sparse signal decomposition and maximum likelihood","authors":"Madhusmita Mohanty, U. Satija, Barathram Ramkumar, M. Manikandan","doi":"10.1109/NCC.2015.7084889","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084889","url":null,"abstract":"In recent years, automatic signal detection and modulation classification play a vital role in the field of cognitive radio applications. The majority of the existing signals detection and classification methods assume that the received signal is contaminated by additive white Gaussian noise. Under impulsive noise condition, the performance of the traditional modulation classification methods may be degraded. Therefore, in this paper, we investigate the application of sparse signal decomposition using an overcomplete dictionary for detection and classification of digital modulation signals. The overcomplete hybrid dictionary consists of impulse waveform and sine and cosine waveform for effectively capturing morphological components of the impulse noise and deterministic modulated signals. The proposed modulation classification method includes the following steps: sparse signal decomposition (SSD) on hybrid dictionaries, modulated signal extraction, matched filtering, and maximum likelihood (ML) classification. The performance of the direct ML and SSD-based ML classification methods are tested and validated using different modulation techniques under different Gaussian and impulse noise conditions. The proposed system achieves a classification accuracy of 89 percent at 0 dB SNR and hence outperforms the direct ML method.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133602432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084885
Rahul Jain, S. De
Determining the optimum multicast parameters is a challenge for point-to-multipoint video/multimedia transmission to a set of users with diverse device capabilities and channel conditions. Recent advancements in H.264/AVC video coding standard allow the users to receive video services based on their terminal capabilities and link quality. In this paper we propose an algorithm to determine the optimum transmission parameters, namely, number of layers and transmission power of each layer, for scalable video multicast over wireless. A utility based approach, that is sensitive to user capabilities and link conditions, is used for power control to deliver best user experience. The algorithm uses discontinuous transmission mode for saving power. An improvement varying from 20% to almost 50% has been observed as compared to the competitive algorithms. Performance improvement is much higher, with an average improvement varying from 40% to almost 100%, when the video is transmitted at higher data rates for short durations, thereby allowing users to save more power and enabling the service providers to make optimal use of system capacity.
{"title":"User-adaptive layer and power allocation for video multicast over wireless","authors":"Rahul Jain, S. De","doi":"10.1109/NCC.2015.7084885","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084885","url":null,"abstract":"Determining the optimum multicast parameters is a challenge for point-to-multipoint video/multimedia transmission to a set of users with diverse device capabilities and channel conditions. Recent advancements in H.264/AVC video coding standard allow the users to receive video services based on their terminal capabilities and link quality. In this paper we propose an algorithm to determine the optimum transmission parameters, namely, number of layers and transmission power of each layer, for scalable video multicast over wireless. A utility based approach, that is sensitive to user capabilities and link conditions, is used for power control to deliver best user experience. The algorithm uses discontinuous transmission mode for saving power. An improvement varying from 20% to almost 50% has been observed as compared to the competitive algorithms. Performance improvement is much higher, with an average improvement varying from 40% to almost 100%, when the video is transmitted at higher data rates for short durations, thereby allowing users to save more power and enabling the service providers to make optimal use of system capacity.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115399659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084841
R. SyamaVarma, K. Sivalingam, Li-Ping Tung, Ying-Dar Lin
This paper presents an analytical model, based on a semi-Markov process, for determining the power savings achieved in a User Equipment (UE) device of a Long Term Evolution (LTE) network using the Discontinuous Reception (DRX) mechanism. Systems with and without packet buffers and the UE and enodeB are presented in this paper. Using the models, it is possible to determine the savings in power attainable by the UE when different DRX sleep cycles and timers are used. The analytical models has been validated using a discrete-event simulation model. The numerical results show that it is possible to obtain UE power savings of up to 63%.
{"title":"Analytical model for power savings in LTE networks using DRX mechanism","authors":"R. SyamaVarma, K. Sivalingam, Li-Ping Tung, Ying-Dar Lin","doi":"10.1109/NCC.2015.7084841","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084841","url":null,"abstract":"This paper presents an analytical model, based on a semi-Markov process, for determining the power savings achieved in a User Equipment (UE) device of a Long Term Evolution (LTE) network using the Discontinuous Reception (DRX) mechanism. Systems with and without packet buffers and the UE and enodeB are presented in this paper. Using the models, it is possible to determine the savings in power attainable by the UE when different DRX sleep cycles and timers are used. The analytical models has been validated using a discrete-event simulation model. The numerical results show that it is possible to obtain UE power savings of up to 63%.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122124647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084853
K. Prahlad, B. Ramamurthi
The radio channel is a critical but independent element affecting a wireless communication system. It is highly time-varying and exhibits behaviors such as path loss, shadowing, multi-path fading and Doppler spread. In this paper, we discuss the design and implementation of a real-time Multi-Terminal Channel Emulator on an SDR (Software Defined Radio) platform for providing controlled variability of channel conditions to test wireless systems. The system design is split into three functions: (i) Channel generation on a PC (ii) Ethernet handling on a DSP (Digital Signal Processor), to receive the channel coefficients and update filters on an FPGA (Field Programmable Gate Array) and (iii) Application of the channel to the data on the FPGA (convolution). We propose a simple technique, where the unit can be used to emulate multiple user scenarios by just modifying the channel generation on the PC. This enables a single hardware unit to emulate multiple users with independent channels.
{"title":"Design and implementation of a Multi-Terminal Channel Emulator on LTE TestBed","authors":"K. Prahlad, B. Ramamurthi","doi":"10.1109/NCC.2015.7084853","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084853","url":null,"abstract":"The radio channel is a critical but independent element affecting a wireless communication system. It is highly time-varying and exhibits behaviors such as path loss, shadowing, multi-path fading and Doppler spread. In this paper, we discuss the design and implementation of a real-time Multi-Terminal Channel Emulator on an SDR (Software Defined Radio) platform for providing controlled variability of channel conditions to test wireless systems. The system design is split into three functions: (i) Channel generation on a PC (ii) Ethernet handling on a DSP (Digital Signal Processor), to receive the channel coefficients and update filters on an FPGA (Field Programmable Gate Array) and (iii) Application of the channel to the data on the FPGA (convolution). We propose a simple technique, where the unit can be used to emulate multiple user scenarios by just modifying the channel generation on the PC. This enables a single hardware unit to emulate multiple users with independent channels.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129326547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084827
S. Gullapally, S. R. Malireddi, S. Raman
We consider the problem of separating static and dynamic regions of a scene when the camera also undergoes motion while capturing still images. We assume that we do not have any other information about the scene and the camera settings. Given two images, we would like to estimate the static and dynamic regions corresponding to one image with respect to the other image. The proposed solution involves over-segmentation of the image and dense correspondence between the two images. We show that the proposed approach works well even when there are changes in illumination and exposure settings while capturing the two images. We evaluate the performance of the proposed approach by demonstrating the results on different scenes with complex object motions.
{"title":"Dynamic object localization using hand-held cameras","authors":"S. Gullapally, S. R. Malireddi, S. Raman","doi":"10.1109/NCC.2015.7084827","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084827","url":null,"abstract":"We consider the problem of separating static and dynamic regions of a scene when the camera also undergoes motion while capturing still images. We assume that we do not have any other information about the scene and the camera settings. Given two images, we would like to estimate the static and dynamic regions corresponding to one image with respect to the other image. The proposed solution involves over-segmentation of the image and dense correspondence between the two images. We show that the proposed approach works well even when there are changes in illumination and exposure settings while capturing the two images. We evaluate the performance of the proposed approach by demonstrating the results on different scenes with complex object motions.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134275467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084876
S. Mandal, S. Prasanna, S. Sundaram
Hidden Markov Models (HMM) are used in handwritten strokes recognition task. The two design parameters of HMM are the number of states and number of mixtures in each state. There are two approaches for finding the number of states, namely, equal number of states and variable number of states. Since the shape of strokes will be different, variable number of states approach should be beneficial. This work proposes a curvature point detection based method to predict variable number of states for modeling a handwritten stroke. The proposed method selects appropriate points from a trace so that the portion between two consecutive points is modeled as an HMM state. Accordingly, based upon handwritten stroke shape complexity, the number of appropriate points selected will change and hence the number of states assigned to the corresponding stroke. In the proposed method, the number of states is proportional to the shape complexity of the given stroke as opposed to fixed in case of brute-force. The HMM based stroke recognizer consisting of 181 distinct strokes, was trained on a set of 52,977 examples collected from approximately 100 native Assamese writers. The evaluation was done on 43,828 examples collected from same users in different sessions. The experimental results demonstrate the benefits of the proposed technique over the brute-force method, especially in case of complex shape strokes.
{"title":"Curvature point based HMM state prediction for online handwritten assamese strokes recognition","authors":"S. Mandal, S. Prasanna, S. Sundaram","doi":"10.1109/NCC.2015.7084876","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084876","url":null,"abstract":"Hidden Markov Models (HMM) are used in handwritten strokes recognition task. The two design parameters of HMM are the number of states and number of mixtures in each state. There are two approaches for finding the number of states, namely, equal number of states and variable number of states. Since the shape of strokes will be different, variable number of states approach should be beneficial. This work proposes a curvature point detection based method to predict variable number of states for modeling a handwritten stroke. The proposed method selects appropriate points from a trace so that the portion between two consecutive points is modeled as an HMM state. Accordingly, based upon handwritten stroke shape complexity, the number of appropriate points selected will change and hence the number of states assigned to the corresponding stroke. In the proposed method, the number of states is proportional to the shape complexity of the given stroke as opposed to fixed in case of brute-force. The HMM based stroke recognizer consisting of 181 distinct strokes, was trained on a set of 52,977 examples collected from approximately 100 native Assamese writers. The evaluation was done on 43,828 examples collected from same users in different sessions. The experimental results demonstrate the benefits of the proposed technique over the brute-force method, especially in case of complex shape strokes.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134432762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084874
S. Singh, R. Manivasakan
We analyze the performance of virtual optical bus (VOB) networks, which is a packet-oriented all-optical solution for transport networks. VOB groups the flows into clusters and coordinates their packets within each cluster in order to minimize the packet collision in the network. We theoretically study the multiplexing (grouping) of packets of flows in a VOB, by modeling a VOB node, in a VOB network, as a queuing system. We derive the expression for the packet loss rate due to inter-VOB collisions, and compare the performance (packet loss rate) of VOB with that of Optical Burst Switching (OBS). We show that the packet loss rate for VOB is upper bounded by the packet/burst loss rate of OBS.
{"title":"Performance analysis of virtual optical bus networks","authors":"S. Singh, R. Manivasakan","doi":"10.1109/NCC.2015.7084874","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084874","url":null,"abstract":"We analyze the performance of virtual optical bus (VOB) networks, which is a packet-oriented all-optical solution for transport networks. VOB groups the flows into clusters and coordinates their packets within each cluster in order to minimize the packet collision in the network. We theoretically study the multiplexing (grouping) of packets of flows in a VOB, by modeling a VOB node, in a VOB network, as a queuing system. We derive the expression for the packet loss rate due to inter-VOB collisions, and compare the performance (packet loss rate) of VOB with that of Optical Burst Switching (OBS). We show that the packet loss rate for VOB is upper bounded by the packet/burst loss rate of OBS.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"1073 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116294509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084855
Priya Singhal, Parag Aggarwal, V. Bohara
We investigate the effects of nonlinear distortion on a carrier aggregated orthogonal frequency division multiplexed (OFDM) signal when it is transmitted through the concurrent dual band nonlinear high power amplifier. Theoretical analysis shows that the signal at the receiver comprises of the original transmitted signal multiplied by the complex phase shift, Gaussian nonlinear noise term and inherent additive white Gaussian noise (AWGN). The mathematical expressions for the Gaussian nonlinear noise due to inter channel interference and the complex phase shift due to channel impairments are derived. The output signal to noise ratio is evaluated from the derived expressions and hence symbol error rate (SER) for M-QAM is calculated theoretically. The simulations for SER using different power amplifier models are also presented to corroborate the theoretical analysis.
{"title":"Analysis of carrier aggregated OFDM signals in presence of dual band power amplifiers","authors":"Priya Singhal, Parag Aggarwal, V. Bohara","doi":"10.1109/NCC.2015.7084855","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084855","url":null,"abstract":"We investigate the effects of nonlinear distortion on a carrier aggregated orthogonal frequency division multiplexed (OFDM) signal when it is transmitted through the concurrent dual band nonlinear high power amplifier. Theoretical analysis shows that the signal at the receiver comprises of the original transmitted signal multiplied by the complex phase shift, Gaussian nonlinear noise term and inherent additive white Gaussian noise (AWGN). The mathematical expressions for the Gaussian nonlinear noise due to inter channel interference and the complex phase shift due to channel impairments are derived. The output signal to noise ratio is evaluated from the derived expressions and hence symbol error rate (SER) for M-QAM is calculated theoretically. The simulations for SER using different power amplifier models are also presented to corroborate the theoretical analysis.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117017671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-16DOI: 10.1109/NCC.2015.7084866
K. Ganguli, P. Rao
The melodic phrases of a raga are an important cue to its identity. Artists, however, incorporate considerable creative variation within a raga phrase during performance while still preserving its identity in the ears of the listeners. It is of interest therefore to explore the boundaries of this categorization of phrase identity, given the space of musical variations in the tonal interval and duration dimensions. Such an endeavor can help better model musical similarity for music retrieval and pedagogy applications. In this work, we carry out melodic shape manipulations on a selected prominent phrase of raga Deshkar to study the subjective responses of musicians in comparison with non-musicians in terms of perceived discrimination of the controlled variations. A method is presented for deriving musically consistent synthetic stimuli for listening. Subjective responses on the discrimination and identification tasks are presented along with a discussion on possible perceptual mechanisms at play.
{"title":"Discrimination of melodic patterns in indian classical music","authors":"K. Ganguli, P. Rao","doi":"10.1109/NCC.2015.7084866","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084866","url":null,"abstract":"The melodic phrases of a raga are an important cue to its identity. Artists, however, incorporate considerable creative variation within a raga phrase during performance while still preserving its identity in the ears of the listeners. It is of interest therefore to explore the boundaries of this categorization of phrase identity, given the space of musical variations in the tonal interval and duration dimensions. Such an endeavor can help better model musical similarity for music retrieval and pedagogy applications. In this work, we carry out melodic shape manipulations on a selected prominent phrase of raga Deshkar to study the subjective responses of musicians in comparison with non-musicians in terms of perceived discrimination of the controlled variations. A method is presented for deriving musically consistent synthetic stimuli for listening. Subjective responses on the discrimination and identification tasks are presented along with a discussion on possible perceptual mechanisms at play.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130308132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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