# Perceptual Characteristics of Voice Identification in Noisy Environments
## 4 Discussion
### Impact of Frequency Distribution  
Different frequency distributions of speech noise affect voice identity perception in low SNR (<0 dB) environments. After removing some frequency bands, the interference of speech noise will reduce, and the perceptional accuracy will increase. This is because the energy of the corresponding frequency band in the voice relatively improves, so the perception performance improves. Among them, the 2930-6250 Hz speech noise has little  
Figure 7: Comparison of auditory analysis and acoustic measurements. impact, and the perception result of the speech noise removing this frequency is close to the unprocessed speech noise. The perceived results in speech noise when removing the 300-640 Hz, 640-1370 Hz, and 1370-2930 Hz frequency bands are more obvious than the unprocessed speech noise. The energy of the Mandarin voice is concentrated in the frequency band of 0-4000 Hz [27]. At the same time, when the sound frequency is close to the frequency of the masking sound, the masking effect is more apparent, and the effect of high-frequency sound's ability to mask low-frequency sound is weak [28]. It also proves our previous conjecture that speech noise significantly impacts voice identity perception because its energy is concentrated in the low-frequency and medium-frequency bands, which is similar to voice frequency areas. The improvement of the perceptional accuracy in low-SNR speech noises varies with the change in the frequency distribution. (1) When the SNR is relatively high (\(-4\) dB), the impact of the 640-1370 Hz speech noise is more obvious. The perception accuracy in speech noise removing these frequency bands is about 0.04 higher than the accuracy of unprocessed speech noise. The 300-640 Hz and 1370-2930 Hz speech noises have similar effects, increasing by approximately 0.02 when removing them from speech noise. However, the perception results in speech noise when removing 2930-6250 Hz frequency band are almost the same as that of unprocessed speech noise. Thus, the perceptual clue for voice identity recognition under this SNR is mainly obtained from voice information below 3000 Hz. (2) When the SNR is relatively low (\(-8\) dB), the influence of 300-640 Hz, 640-1370 Hz, and 1370-2930 Hz speech noises is similar. The accuracy improves by about 0.10 after removing them from speech noise. Furthermore, the perception result of speech noise when removing the 2930-6250 Hz frequency band is about 0.04 higher than that of unprocessed speech noise. Compared with the perceptual results of this frequency band at \(-4\) dB, the 2930-6250 Hz frequency band has an increased impact on voice identity perception. That is, the voice information in the 2930-6250 Hz frequency band helps improve the accuracy of voice identity perception under this SNR environment. As a consequence, it may be inferred that voice identity perception in a better voice transmission environment is mainly based on the acoustic information provided by the low-frequency and medium-frequency bands, which concentrate most of the energy of the voice. As the SNR gradually decreases, a human's auditory mechanism will automatically expand the receiving frequency range to obtain more effective acoustic information from the high-frequency band. The high-frequency information ignored in the objective algorithm may be more robust to identity perception in our environment. Previously, our research team obtained similar results in cross-lingual speaker voice perception research. The difference in voice timbre under noiseless and noisy conditions was concentrated in the high frequency (>4 KHz). In other words, high-frequency voice information has some role in recognizing voice identity [29]. It is known that the low-frequency and medium-frequency bands mainly contain acoustic information from vowels, whereas high-frequency bands provide acoustic information from consonants.