## 3 Evaluation
### Subjective Localization Experiments  
A localization experiment was further undertaken to verify the effectiveness of the proposed hybrid algorithm subjectively. Six graduate students (from 22 to 27 years old) participated in the experiment. They have experience in sound localization experiments and been screened by the Orbiter medical audiometer with a hearing loss of less than 10 dBHL below 8 kHz and less than 15 dBHL from 8 kHz to 12.5 kHz. The anthropometric parameters of the six subjects were extracted using the anthropometric parameter extraction method based on the three-dimensional scanned head model [35]. Dimensions of the measured anthropometric parameters of these six subjects are shown in Table 6. The predicted HRTFs were reconstructed by substituting the extracted anthropometric parameters into the regression formulas in Table 4.  
In terms of experimental signals, the predicted HRIR and KEMAR HRIR were separately convoluted with a white noise to obtain the binaural signals for rendering. Specifically, the white noise is 10 s with the sampling resolution of 44,100 Hz and the quantization resolution of 16 bits. Note that the predicted HRIR and KEMAR HRIR signals used here are the minimum phase functions, which are determined by the magnitudes of the predicted and KEMAR HRTFs, respectively. The target sound direction is selected from the median plane of six elevations: \(-45^{\circ}\), \(0^{\circ}\), \(22.5^{\circ}\), \(45^{\circ}\), \(67.5^{\circ}\), and \(90^{\circ}\). Each subject needed to make 72 judgments (six source directions \(\times\) two HRTF types \(\times\) six repetitions). For each experimental condition, there were 36 judgments (six subjects \(\times\) six repetitions). All the signal segments were presented randomly to each subject. The experimental hardware platform was a Windows 7 platform-based computer, the sound card was ESI(r) maya22 usb, and the headset was a pair of Sennheiser IE 80. As our work focuses on the vertical localization in the median plane, the median-plane coordinates were arranged with elevation angles labelled at intervals of \(5^{\circ}\). Before the experiment, the subject's head was aligned to the center of the median-plane coordinates. In the experiment, the subject held a laser pen, and pointed to the perceived direction of sound source by straightening his/her arm. Then, the elevation angle of the perceived sound source was read and recorded by the experimenter. Playback was allowed until the subject determined the perceived directions and no feedback was provided to the subject. Figure 8: Mean spectral distortion of the validation group at 25 elevations in the median plane. Table 7 shows the experimental results of the six subjects. The absolute angle error is defined as the absolute value of the difference between the direction judged by the subject and the preset target direction. The table shows the average angle error from 36 judgments. Note that the angle errors were calculated after correcting for front-back and up-down confusions [2]. As to the absolute angle error, the HRTFs predicted by the proposed algorithm demonstrate a better localization effect than the KEMAR HRTFs in all of the six test directions. A further \(t\)-test shows that there is a significant difference in localization performance at elevations of 0\({}^{\circ}\) and 22.5\({}^{\circ}\) (\(p<0.01\)) and elevations of 45\({}^{\circ}\), 67.5\({}^{\circ}\), and 90\({}^{\circ}\) (\(p<0.05\)), whereas no significant difference is observed at the elevation of \(-45^{\circ}\) (\(p>0.05\)). For the front-back and up-down confusion rates, the predicted HRTF of the proposed algorithm is 5.5% and 3.3% lower than those of the KEMAR HRTFs, respectively. In summary, the proposed HRTF customization hybrid algorithm based on ICA decomposition and anthropometric parameter measurement is effective compared with KEMAR HRTFs with respect to both objective and subjective evaluations. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\mathbf{X}\) & **No. 1** & **No. 2** & **No. 3** & **No.