## 3 Experiments
### Ortolan Bunting (Emberiza Hortulana): Syllable, Song Variant, and Song Type Classification  
The ortolan bunting is an endangered migratory passerine distributed from Western Europe to Mongolia [42], which has undergone a major population decline in recent years [43,44]. This bird vocalizes in a range between 1.9 kHz and 6.7 kHz and has a relatively simple song and a repertoire size that varies between just a few songs per individual to as many as 24 [45]. The ortolan bunting vocalizations examined for this study were collected from County Hedmark, Norway in May of 2001 and 2002 [46]. The male vocalizations were recorded on 11 out of 25 sites within an area of about 500 km\({}^{2}\). The total number of males in the covered area during 2001 and 2002 was approximately 150. As described by [PERSON] [46], these ortolan vocalizations were recorded between 04:00 and 11:00 am with a professional DAT recorder at the sampling rate of 48 kHz. Songs of ortolan buntings are composed of base units referred to as syllables. Each syllable is described using letter notation, as illustrated in Figure 4. Songs are categorized by song type, defined according to the general type of syllable pattern, and further into specific song variants, defined by exact repetition pattern. For example, common song types include _ab_, _cd_, and _huf_, with common song variants such as _aaaab_, _aaaaabb_, _cccd_, and _hhhhuff_. Although individual examples of syllables differ in length and frequency across individuals, they maintain the same sonogram shape and underlying temporal pattern. \begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|c|} \hline \hline  & & \multicolumn{6}{c|}{**Classification**} \\ \cline{3-8}  & & **BRK** & **ROR** & **RUM** & **SQK** & **SQL** & **TMP** \\ \cline{2-8}  & BRK & 15 & 0 & 0 & 0 & 4 & 3 \\ \cline{2-8}  & ROR & 3 & 22 & 0 & 0 & 1 & 0 \\ \cline{2-8}  & **RUM** & 1 & 2 & 4 & 0 & 0 & 1 \\ \cline{2-8}  & **SQK** & 0 & 0 & 0 & 60 & 1 & 0 \\ \cline{2-8}  & **SQL** & 0 & 1 & 0 & 1 & 26 & 2 \\ \cline{2-8}  & **TMP** & 0 & 2 & 0 & 3 & 3 & 31 \\ \hline \end{tabular}
\end{table} 
Table 2: Call type classification accuracy over reduced-set clean Asian Elephant data. Overall accuracy is 85.0% (_vs_. chance accuracy 32.8%). This study focuses on automatic song classification in the ortolan hunting. Modeling is done at the syllable level, so that each syllable type has a corresponding HMM, and then classifying into a syllable sequence to match individual songs with a specific song type and song variant. To evaluate classification accuracy using HMMs, a subset of 10 frequently produced call types is used, with 25 calls in each type used for training and 25 for testing, and data across multiple individuals included in both the training and test sets. The call types selected include _ab_, _cb_, _cd_, _eb_, _ef_, _gb_, _guf_, \(h\), _huf_, and _jufb_, which consist of the ten common syllables \(a\), \(b\), \(c\), \(d\), \(e\), \(f\), \(g\), \(h\), \(j\), and \(u\). In addition a silence model is trained to represent beginning and ending silence and pauses between syllables. Due to substantial recording noise, all waveforms are enhanced using simple band-pass filtering to eliminate noise outside the active vocalization range (2,500 to 7,500 Hz) of these calls, followed by Ephraim-Malah filtering [18], a statistical signal enhancement method common in human speech processing applications. Analysis is then done using Hamming windows with a window size of 5 ms with 2.5 ms overlap, accounting for the much faster temporal patterns present in the hunting vocalizations as compared to the Asian elephants. Features for classification are the same 39 element GFCC feature vector described previously for the Asian elephant data, with a few minor differences. The main difference is that the lower and upper frequency limits of the Greenwood function used for frequency warping are adjusted to 2,500 and 7,500 Hz, respectively, to represent the frequency range of these calls.