This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for professionals and researchers in musical signal processing.
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1 | (16) |
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1 | (1) |
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2 | (1) |
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3 | (4) |
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1.3.1 Notes (Swara) in Indian Music |
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5 | (1) |
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1.3.2 Importance of the Tonic (Sa) |
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6 | (1) |
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1.4 Basic Elements of Music |
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7 | (1) |
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1.5 Uniqueness of Indian Classical Music |
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8 | (1) |
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1.6 Different Forms of Indian Classical Music |
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9 | (3) |
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1.7 Raga---The Soul of Indian Classical Music |
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12 | (1) |
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1.8 Scientific Research in Indian Music |
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13 | (4) |
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15 | (2) |
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2 Music Information Retrieval |
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17 | (18) |
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17 | (1) |
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18 | (8) |
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2.2.1 Process of Feature Extraction |
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19 | (3) |
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2.2.2 Selection of Features |
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22 | (4) |
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2.3 Conclusions and Discussion |
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26 | (9) |
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30 | (5) |
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3 Scales and Shruti Concept |
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35 | (24) |
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35 | (3) |
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38 | (3) |
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41 | (3) |
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42 | (1) |
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42 | (1) |
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42 | (2) |
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44 | (15) |
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3.4.1 Objective Modeling of Musical Scale |
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46 | (1) |
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3.4.2 Relevant Psycho-Perceptual Concepts |
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47 | (2) |
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49 | (1) |
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3.4.4 Construction of Shrutis from Hypothesis |
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50 | (6) |
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56 | (1) |
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56 | (3) |
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4 Tonic Detection and Shruti Analysis from Raga Performance |
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59 | (24) |
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59 | (2) |
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4.2 Relevant Signal Processing |
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61 | (3) |
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4.2.1 Pitch Period Extraction from Signal |
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61 | (1) |
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62 | (1) |
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4.2.3 Steady State Detection |
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63 | (1) |
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4.3 Determination of Tonic (Sa) |
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64 | (5) |
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65 | (1) |
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4.3.2 Experimental Details |
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65 | (2) |
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4.3.3 Results and Discussions |
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67 | (2) |
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4.4 Swara-Shruti Relation |
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69 | (1) |
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4.5 Ratio-Intervals for Steady States |
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69 | (4) |
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71 | (1) |
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71 | (1) |
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4.5.3 Results and Discussions |
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72 | (1) |
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4.6 Shruti Positions in Contemporary Performances |
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73 | (4) |
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4.6.1 Clustering Methodology |
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74 | (1) |
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4.6.2 Algorithm (K-Means) |
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75 | (1) |
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76 | (1) |
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4.7 Approach of Heuristic Search |
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77 | (4) |
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77 | (1) |
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4.7.2 Results and Discussions |
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78 | (3) |
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81 | (2) |
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81 | (2) |
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5 Pitch Transition and Pitch Stability |
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83 | (18) |
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83 | (2) |
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85 | (1) |
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5.3 Algorithmic Procedure |
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85 | (2) |
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87 | (7) |
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5.4.1 Objective Categorisation of Meends |
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89 | (1) |
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89 | (2) |
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5.4.3 More Details on Intonation |
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91 | (1) |
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92 | (1) |
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93 | (1) |
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5.5 On Perceptibility of Transitory Movements |
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94 | (2) |
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5.5.1 Experimental Procedure |
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94 | (2) |
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5.6 Results and Discussions |
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96 | (2) |
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98 | (1) |
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99 | (2) |
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99 | (2) |
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101 | (24) |
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101 | (1) |
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6.2 Swars or Notes (To Be Used in Ragas) |
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101 | (3) |
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102 | (1) |
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6.2.2 Quantified Features of Raga |
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102 | (2) |
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104 | (4) |
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6.3.1 Process of Feature Extraction and Database Building |
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104 | (4) |
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108 | (4) |
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6.5 Experiments and Results |
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112 | (3) |
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6.5.1 Experimental Parameters |
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112 | (1) |
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112 | (1) |
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6.5.3 Identification Accuracy |
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112 | (1) |
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6.5.4 Identification Versus Accuracy |
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113 | (2) |
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115 | (3) |
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6.6.1 Experimental Details |
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115 | (1) |
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116 | (2) |
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6.7 Identification of Raga |
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118 | (7) |
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120 | (2) |
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6.7.2 Results and Discussion |
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122 | (1) |
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123 | (2) |
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125 | (18) |
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125 | (3) |
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125 | (1) |
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7.1.2 Gharana Identification |
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126 | (2) |
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128 | (4) |
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7.2.1 Timbral Texture Features |
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129 | (1) |
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130 | (2) |
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132 | (1) |
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7.4 Feature Database Preparation |
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133 | (3) |
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7.5 Experimental Results and Discussions |
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136 | (4) |
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140 | (3) |
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141 | (2) |
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8 Production, Perception and Cognition |
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143 | (24) |
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143 | (1) |
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144 | (3) |
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147 | (13) |
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8.3.1 Significance of Cognition |
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149 | (1) |
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8.3.2 Some Experiments in Aural Cognition |
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150 | (6) |
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156 | (4) |
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160 | (7) |
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164 | (3) |
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9 Automatic Musical Instrument Recognition |
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167 | (66) |
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168 | (9) |
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168 | (1) |
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9.1.2 Indian Musical Instruments |
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168 | (1) |
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169 | (3) |
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172 | (1) |
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173 | (1) |
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174 | (1) |
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175 | (2) |
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9.2 Acoustical Analysis for the Sound of Indian Musical Instruments |
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177 | (38) |
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177 | (1) |
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178 | (2) |
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9.2.3 Perceptual Features |
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180 | (1) |
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181 | (1) |
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9.2.5 Wavelet Analysis (Transform) |
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181 | (2) |
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183 | (2) |
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9.2.7 Analysis of Acoustic Characteristics of Musical Instrument from Their Sound Signals |
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185 | (26) |
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211 | (4) |
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9.3 Identification of Indian Musical Instruments |
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215 | (18) |
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215 | (1) |
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9.3.2 Sound Source Recognition by Human Brain |
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216 | (2) |
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218 | (1) |
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9.3.4 Important Features for Musical Instrument Recognition Systems |
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218 | (1) |
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9.3.5 Temporal Envelope Estimation |
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219 | (1) |
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219 | (1) |
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220 | (8) |
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228 | (2) |
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230 | (1) |
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230 | (3) |
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10 Vadi-Samvadi Controversy and Statistics |
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233 | (16) |
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233 | (2) |
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235 | (1) |
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10.2.1 Krumhansl's Method |
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235 | (1) |
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10.3 Experimental Results and Discussions |
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236 | (11) |
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236 | (6) |
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242 | (5) |
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247 | (2) |
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247 | (2) |
| Epilogue |
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249 | |
Prof. Asoke Kumar Datta, an MSc. (Pure Math), worked in Indian Statistical Institute 1955-1994, retired as HOD Electronics and Communication Sciences Department, Visiting Professor of ISI till date; President, BOM-BOM, Kolkata; Senior Guest Researcher, Sir C V Raman Centre for Physics and Music, JU; Executive Member, Society for Natural Language Technology Research, Kolkata; Life Member, Acoustical Society of India; J C Bose Memorial Award, 1969, Sir C V Raman Award, 1982-83 &1998-99, S K Mitra Memorial Award, 1984, Sri C AchyutMenon Prize, 2001; Area of Academic interest- Pattern Recognition, AI, Speech, Music and Consciousness; Hobbies: Water colour, Sculpture.
Dr. Sandeep Singh Solanki, a PhD in Engineering and Master of Engineering in Instrumentation, is currently a Professor in the Department of ECE BIT Mesra, Ranchi, India. His research interest is in the field of Speech and Music Signal Processing and Automation. He has sixteen years of teaching and six years of Industrial experience. He has published several research papers in the area of Music signal processing, Sensors development in addition to one book.
Dr. Ranjan Sengupta, a PhD in High energy Physics, was the Senior Research Scientist and Head,Scientific Research Department, ITC Sangeet Research Academy, Kolkata for 27 years. From 2010 he is associated with Sir C V Raman Centre of Physics and Music, Jadavpur University, Kolkata as a Scientific Consultant. He has published more than 150 papers in the area of High Energy Physics, Music Signal Processing, Speaker Recognition, Music Information Retrieval, Music Perception andCognition and Music Acoustics. He is a recipient of Sir C V Raman Award from Acoustical Society of India. A Life Fellow of the Acoustical Society of India, he is also a life member of Indian Physical Society and Indian Association for the Cultivation of Science, Kolkata.
Dr. Soubhik Chakraborty, a PhD in Statistics, is currently a Professor in the Deptartment of Mathematics, BIT Mesra, Ranchi, India. His research interest is in the field of Algorithm Analysis and Music Analysis. He has published several research papers in this area in addition to four books. He is an acknowledged reviewer of IEEE, ACM and AMM (for the journals Transactions on Computers, Computing Reviews and Mathematical Reviews, respectively). He is a recipient of several awards in both teaching and research e.g. National Award for Teaching Excellence (Mathematics) given by Indus Foundation and Best Academic Researcher Award given by ASDF, Shiksha Rattan Puraskar, Rajiv Gandhi Excellence Award, Glory of India Award (IIFS), Glory of India Gold Medal (IISA) and Best Educationist Award (IIEM). A life member of Indian Statistical Institute, Acoustical Society of India and Association of Computer, Electronics and Electrical Engineers, he is also a Harmonium Player.
Dr. Kartik Mahto, a PhD in Engineering and Master of Engineering in Control Systems, is currently an Assistant Professor in the Dept. of ECE BIT Mesra, Ranchi, India. His research interest is in the field of Musical Signal Processing and Instrumentation. He has thirteen years of teaching and five years of research experience. He has published several research papers in the area of Music signal processing.
Anirban Patranabis, MSc, PhD (Physics) is attached to Sir C V Raman Centre for Physics and Music,Jadavpur University, Kolkata. He is an assistant Teacher in Physics at Bamanpukuria S M M HighSchool. He has many publications in the area of music signal processing in national and international journals.
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