Name
Title | ||
|---|---|---|
Bird Call Identification Using Dynamic Kernel Based Support Vector Machines and Deep Neural Networks |
Abstract | ||
|---|---|---|
In this paper, we apply speech and audio processing techniques to bird vocalizations and for the classification of birds found in the lower Himalayan regions. Mel frequency cepstral coefficients (MFCC) are extracted from each recording. As a result, the recordings are now represented as varying length sets of feature vectors. Dynamic kernel based support vector machines (SVMs) and deep neural networks (DNNs) are popularly used for the classification of such varying length patterns obtained from speech signals. In this work, we propose to use dynamic kernel based SVMs and DNNs for classification of bird calls represented as sets of feature vectors. Results of our studies show that both approaches give comparable performance. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICMLA.2016.0053 | 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA) |
Keywords | Field | DocType |
Bio-acoustics,bird call identification,dynamic kernels,support vector machines,deep neural networks | Mel-frequency cepstrum,Computer science,Artificial intelligence,Probabilistic logic,Audio signal processing,Artificial neural network,Deep neural networks,Kernel (linear algebra),Feature vector,Pattern recognition,Support vector machine,Speech recognition,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-5090-6168-6 | 1 | 0.36 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Deep Chakraborty | 1 | 1 | 0.36 |
| Paawan Mukker | 2 | 1 | 0.36 |
| Padmanabhan Rajan | 3 | 22 | 7.63 |
| A. D. Dileep | 4 | 15 | 7.72 |