BioAcoustica is a free, open repository of wildlife sound recordings from the Natural History Museum, London.
Taxonomic index of the BioAcoustica collection
Acoustic and biological measurements in the BioAcoustica collection
Recording annotations from ann-o-mate
The specimens that recordings are of, from the collections
Lee, Chang-Hsing; Chou, Chih-Hsun; Han, Chin-Chuan; Huang, Ren-Zhuang (2006). Automatic recognition of animal vocalizations using averaged MFCC and linear discriminant analysis. Pattern Recognition Letters, 27(2): 93 - 101.
In this paper we propose a method that uses the averaged Mel-frequency cepstral coefficients (MFCCs) and linear discriminant anal- ysis (LDA) to automatically identify animals from their sounds. First, each syllable corresponding to a piece of vocalization is segmented. The averaged MFCCs over all frames in a syllable are calculated as the vocalization features. Linear discriminant analysis (LDA), which finds out a transformation matrix that minimizes the within-class distance and maximizes the between-class distance, is utilized to increase the classification accuracy while to reduce the dimensionality of the feature vectors. In our experiment, the average classification accuracy is 96.8% and 98.1% for 30 kinds of frog calls and 19 kinds of cricket calls, respectively.
| Anura |
| Orthoptera |
Where the specimens that recordings are of were collected, not where the sound was recorded