Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (12): 3906-3912.DOI: 10.11772/j.issn.1001-9081.2021101816
• Multimedia computing and computer simulation • Previous Articles Next Articles
Yijie LIU1, Jiangchun LI2, Weina CHEN1(), Qihan HUANG1
Received:
2021-10-26
Revised:
2022-01-10
Accepted:
2022-01-24
Online:
2022-04-08
Published:
2022-12-10
Contact:
Weina CHEN
About author:
LIU Yijie, born in 1996, M. S. candidate. His research interests include forensic speaker comparison.Supported by:
通讯作者:
陈维娜
作者简介:
刘贻杰(1996—),男,广东茂名人,硕士研究生,主要研究方向:声纹检验基金资助:
CLC Number:
Yijie LIU, Jiangchun LI, Weina CHEN, Qihan HUANG. Influence of channel on formant of vowel in Chinese mandarin[J]. Journal of Computer Applications, 2022, 42(12): 3906-3912.
刘贻杰, 李江春, 陈维娜, 黄颀涵. 信道对汉语普通话元音共振峰的影响[J]. 《计算机应用》唯一官方网站, 2022, 42(12): 3906-3912.
Add to citation manager EndNote|Ris|BibTeX
URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2021101816
志愿者 | 性别 | 出生年份 | 民族 | 籍贯 |
---|---|---|---|---|
1 | 男 | 1997 | 汉 | 河北 |
2 | 男 | 1995 | 汉 | 山东 |
3 | 男 | 1997 | 汉 | 山东 |
4 | 男 | 1997 | 汉 | 山东 |
5 | 男 | 1997 | 汉 | 河北 |
6 | 女 | 1997 | 汉 | 陕西 |
7 | 女 | 1997 | 汉 | 陕西 |
8 | 女 | 1996 | 汉 | 河南 |
Tab.1 Brief information of 8 volunteers
志愿者 | 性别 | 出生年份 | 民族 | 籍贯 |
---|---|---|---|---|
1 | 男 | 1997 | 汉 | 河北 |
2 | 男 | 1995 | 汉 | 山东 |
3 | 男 | 1997 | 汉 | 山东 |
4 | 男 | 1997 | 汉 | 山东 |
5 | 男 | 1997 | 汉 | 河北 |
6 | 女 | 1997 | 汉 | 陕西 |
7 | 女 | 1997 | 汉 | 陕西 |
8 | 女 | 1996 | 汉 | 河南 |
编号 | 信道 | 端到端 |
---|---|---|
a | 麦克风阵列1 | 讯飞声纹采集仪→PC端 |
b | 麦克风阵列2 | 国音声纹采集仪→PC端 |
c | 2G GSM移动通话 | 诺基亚→荣耀honor 20i |
d | 4G VoLTE移动通话 | 荣耀honor 20i→华为Mate30 Pro(5G) |
e | 5G VoNR移动通话 | 华为Mate30 Pro(5G)→ 华为Mate30 Pro(5G) |
f | “微信”语音消息 | 荣耀honor 20i→PC端 |
g | “微信”语音通话 | 荣耀honor 20i→PC端 |
h | “QQ”语音消息 | 荣耀honor 20i→PC端 |
i | “QQ”语音通话 | 荣耀honor 20i→PC端 |
j | “陌陌”语音消息 | 荣耀honor 20i→PC端 |
k | “世纪佳缘”语音消息 | 荣耀honor 20i→iPad Pro |
l | “Skype”语音消息 | 荣耀honor 20i→PC端 |
m | “WhatsApp”语音消息 | 荣耀honor 20i→PC端 |
Tab.2 Detailed information of experimental channels
编号 | 信道 | 端到端 |
---|---|---|
a | 麦克风阵列1 | 讯飞声纹采集仪→PC端 |
b | 麦克风阵列2 | 国音声纹采集仪→PC端 |
c | 2G GSM移动通话 | 诺基亚→荣耀honor 20i |
d | 4G VoLTE移动通话 | 荣耀honor 20i→华为Mate30 Pro(5G) |
e | 5G VoNR移动通话 | 华为Mate30 Pro(5G)→ 华为Mate30 Pro(5G) |
f | “微信”语音消息 | 荣耀honor 20i→PC端 |
g | “微信”语音通话 | 荣耀honor 20i→PC端 |
h | “QQ”语音消息 | 荣耀honor 20i→PC端 |
i | “QQ”语音通话 | 荣耀honor 20i→PC端 |
j | “陌陌”语音消息 | 荣耀honor 20i→PC端 |
k | “世纪佳缘”语音消息 | 荣耀honor 20i→iPad Pro |
l | “Skype”语音消息 | 荣耀honor 20i→PC端 |
m | “WhatsApp”语音消息 | 荣耀honor 20i→PC端 |
信道 | F1 | F2 | F3 | F4 | F5 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | |
总计 | 620 | 624 | 99.4 | 602 | 624 | 96.5 | 495 | 624 | 79.3 | 449 | 624 | 72.0 | 358 | 624 | 57.4 |
a | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 |
b | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 46 | 48 | 95.8 |
c | 44 | 48 | 91.7 | 46 | 48 | 95.8 | 37 | 48 | 77.1 | 8 | 48 | 16.7 | 0 | 48 | 0.0 |
d | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 43 | 48 | 89.6 | 43 | 48 | 89.6 | 38 | 48 | 79.2 |
e | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 44 | 48 | 91.7 | 45 | 48 | 93.8 |
f | 48 | 48 | 100.0 | 39 | 48 | 81.3 | 29 | 48 | 60.4 | 45 | 48 | 93.8 | 26 | 48 | 54.2 |
g | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 46 | 48 | 95.8 | 47 | 48 | 97.9 | 31 | 48 | 64.6 |
h | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 41 | 48 | 85.4 | 40 | 48 | 83.3 | 28 | 48 | 58.3 |
i | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 41 | 48 | 85.4 | 40 | 48 | 83.3 | 23 | 48 | 47.9 |
j | 48 | 48 | 100.0 | 44 | 48 | 91.7 | 10 | 48 | 20.8 | 0 | 48 | 0.0 | 0 | 48 | 0.0 |
k | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 33 | 48 | 68.8 | 12 | 48 | 25.0 | 0 | 48 | 0.0 |
l | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 37 | 48 | 77.1 | 37 | 48 | 77.1 | 43 | 48 | 89.6 |
m | 48 | 48 | 100.0 | 47 | 48 | 97.9 | 37 | 48 | 77.1 | 37 | 48 | 77.1 | 30 | 48 | 62.5 |
Tab.3 Overall form change scores of formants of vowel
信道 | F1 | F2 | F3 | F4 | F5 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | 不变 数量 | 被试 总数 | 占比/ % | |
总计 | 620 | 624 | 99.4 | 602 | 624 | 96.5 | 495 | 624 | 79.3 | 449 | 624 | 72.0 | 358 | 624 | 57.4 |
a | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 |
b | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 46 | 48 | 95.8 |
c | 44 | 48 | 91.7 | 46 | 48 | 95.8 | 37 | 48 | 77.1 | 8 | 48 | 16.7 | 0 | 48 | 0.0 |
d | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 43 | 48 | 89.6 | 43 | 48 | 89.6 | 38 | 48 | 79.2 |
e | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 44 | 48 | 91.7 | 45 | 48 | 93.8 |
f | 48 | 48 | 100.0 | 39 | 48 | 81.3 | 29 | 48 | 60.4 | 45 | 48 | 93.8 | 26 | 48 | 54.2 |
g | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 46 | 48 | 95.8 | 47 | 48 | 97.9 | 31 | 48 | 64.6 |
h | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 41 | 48 | 85.4 | 40 | 48 | 83.3 | 28 | 48 | 58.3 |
i | 48 | 48 | 100.0 | 48 | 48 | 100.0 | 41 | 48 | 85.4 | 40 | 48 | 83.3 | 23 | 48 | 47.9 |
j | 48 | 48 | 100.0 | 44 | 48 | 91.7 | 10 | 48 | 20.8 | 0 | 48 | 0.0 | 0 | 48 | 0.0 |
k | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 33 | 48 | 68.8 | 12 | 48 | 25.0 | 0 | 48 | 0.0 |
l | 48 | 48 | 100.0 | 45 | 48 | 93.8 | 37 | 48 | 77.1 | 37 | 48 | 77.1 | 43 | 48 | 89.6 |
m | 48 | 48 | 100.0 | 47 | 48 | 97.9 | 37 | 48 | 77.1 | 37 | 48 | 77.1 | 30 | 48 | 62.5 |
信道 | F1 | F2 | F3 | F4 | F5 | |||||
---|---|---|---|---|---|---|---|---|---|---|
卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | |
a | / | / | / | / | / | / | / | / | / | / |
b | / | / | / | / | / | / | / | / | 2.043 | 0.153 |
c | 4.174 | 0.041 | 2.043 | 0.153 | 12.424 | 0.000 | 68.571 | 0.000 | — | — |
d | / | / | / | / | 5.275 | 0.022 | 5.275 | 0.022 | 11.163 | 0.001 |
e | / | / | / | / | 3.097 | 0.078 | 4.174 | 0.041 | 3.097 | 0.078 |
f | / | / | 9.931 | 0.002 | 23.688 | 0.000 | 3.097 | 0.078 | 28.541 | 0.000 |
g | / | / | / | / | 2.043 | 0.153 | 1.011 | 0.315 | 20.658 | 0.000 |
h | / | / | / | / | 7.551 | 0.006 | 8.727 | 0.003 | 25.263 | 0.000 |
i | / | / | / | / | 7.551 | 0.006 | 8.727 | 0.003 | 33.803 | 0.000 |
j | / | / | 4.174 | 0.041 | 62.897 | 0.000 | — | — | — | — |
k | / | / | 3.097 | 0.078 | 17.778 | 0.000 | 12.424 | 0.000 | — | — |
l | / | / | 3.097 | 0.078 | 12.424 | 0.000 | 12.424 | 0.000 | 5.275 | 0.022 |
m | / | / | 1.011 | 0.315 | 12.424 | 0.000 | 68.571 | 0.000 | 22.154 | 0.000 |
Tab.4 Chi-square test results of overall forms of formants of vowel in recordings of different channels
信道 | F1 | F2 | F3 | F4 | F5 | |||||
---|---|---|---|---|---|---|---|---|---|---|
卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | 卡方值 | 显著性 | |
a | / | / | / | / | / | / | / | / | / | / |
b | / | / | / | / | / | / | / | / | 2.043 | 0.153 |
c | 4.174 | 0.041 | 2.043 | 0.153 | 12.424 | 0.000 | 68.571 | 0.000 | — | — |
d | / | / | / | / | 5.275 | 0.022 | 5.275 | 0.022 | 11.163 | 0.001 |
e | / | / | / | / | 3.097 | 0.078 | 4.174 | 0.041 | 3.097 | 0.078 |
f | / | / | 9.931 | 0.002 | 23.688 | 0.000 | 3.097 | 0.078 | 28.541 | 0.000 |
g | / | / | / | / | 2.043 | 0.153 | 1.011 | 0.315 | 20.658 | 0.000 |
h | / | / | / | / | 7.551 | 0.006 | 8.727 | 0.003 | 25.263 | 0.000 |
i | / | / | / | / | 7.551 | 0.006 | 8.727 | 0.003 | 33.803 | 0.000 |
j | / | / | 4.174 | 0.041 | 62.897 | 0.000 | — | — | — | — |
k | / | / | 3.097 | 0.078 | 17.778 | 0.000 | 12.424 | 0.000 | — | — |
l | / | / | 3.097 | 0.078 | 12.424 | 0.000 | 12.424 | 0.000 | 5.275 | 0.022 |
m | / | / | 1.011 | 0.315 | 12.424 | 0.000 | 68.571 | 0.000 | 22.154 | 0.000 |
信道 | F1 | F2 | F3 | F4 | F5 | |||||
---|---|---|---|---|---|---|---|---|---|---|
差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | |
a | - | - | - | - | - | - | - | - | - | - |
b | - | - | - | - | - | - | - | - | - | - |
c | + | - | - | - | - | ++ | - | ++ | - | ++ |
d | - | - | - | - | + | - | + | - | - | ++ |
e | - | - | - | - | - | - | + | - | - | - |
f | - | - | - | ++ | - | ++ | - | - | - | ++ |
g | - | - | - | - | - | - | - | - | - | ++ |
h | - | - | - | - | - | ++ | - | ++ | - | ++ |
i | - | - | - | - | - | ++ | - | ++ | - | ++ |
j | - | - | + | - | - | ++ | - | ++ | - | ++ |
k | - | - | - | - | - | ++ | - | ++ | - | ++ |
l | - | - | - | - | - | ++ | - | ++ | + | - |
m | - | - | - | - | - | ++ | - | ++ | - | ++ |
Tab.5 Significance statistics of overall forms of formants of vowel affected by channels
信道 | F1 | F2 | F3 | F4 | F5 | |||||
---|---|---|---|---|---|---|---|---|---|---|
差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | 差异 | 显著差异 | |
a | - | - | - | - | - | - | - | - | - | - |
b | - | - | - | - | - | - | - | - | - | - |
c | + | - | - | - | - | ++ | - | ++ | - | ++ |
d | - | - | - | - | + | - | + | - | - | ++ |
e | - | - | - | - | - | - | + | - | - | - |
f | - | - | - | ++ | - | ++ | - | - | - | ++ |
g | - | - | - | - | - | - | - | - | - | ++ |
h | - | - | - | - | - | ++ | - | ++ | - | ++ |
i | - | - | - | - | - | ++ | - | ++ | - | ++ |
j | - | - | + | - | - | ++ | - | ++ | - | ++ |
k | - | - | - | - | - | ++ | - | ++ | - | ++ |
l | - | - | - | - | - | ++ | - | ++ | + | - |
m | - | - | - | - | - | ++ | - | ++ | - | ++ |
信道 | 不变数量 | 被试数量 | 占比/% |
---|---|---|---|
总计 | 139 | 624 | 22.3 |
a | 45 | 48 | 93.8 |
b | 43 | 48 | 89.6 |
c | 0 | 48 | 0.0 |
d | 9 | 48 | 18.8 |
e | 9 | 48 | 18.8 |
f | 1 | 48 | 2.1 |
g | 7 | 48 | 14.6 |
h | 6 | 48 | 12.5 |
i | 7 | 48 | 14.6 |
j | 0 | 48 | 0.0 |
k | 0 | 48 | 0.0 |
l | 9 | 48 | 18.8 |
m | 3 | 48 | 6.3 |
Tab.6 Scores of relative intensity changes of formants of vowel
信道 | 不变数量 | 被试数量 | 占比/% |
---|---|---|---|
总计 | 139 | 624 | 22.3 |
a | 45 | 48 | 93.8 |
b | 43 | 48 | 89.6 |
c | 0 | 48 | 0.0 |
d | 9 | 48 | 18.8 |
e | 9 | 48 | 18.8 |
f | 1 | 48 | 2.1 |
g | 7 | 48 | 14.6 |
h | 6 | 48 | 12.5 |
i | 7 | 48 | 14.6 |
j | 0 | 48 | 0.0 |
k | 0 | 48 | 0.0 |
l | 9 | 48 | 18.8 |
m | 3 | 48 | 6.3 |
信道 | 皮尔逊卡方 | 渐进显著性(双侧) |
---|---|---|
a | 3.097 | 0.078 |
b | 5.275 | 0.022 |
d | 65.684 | 0.000 |
e | 65.684 | 0.000 |
f | 92.082 | 0.000 |
g | 71.564 | 0.000 |
h | 74.667 | 0.000 |
i | 71.564 | 0.000 |
l | 65.684 | 0.000 |
m | 84.706 | 0.000 |
Tab.7 Chi-square test results of the relative intensity of selected voice segments in each channel recording
信道 | 皮尔逊卡方 | 渐进显著性(双侧) |
---|---|---|
a | 3.097 | 0.078 |
b | 5.275 | 0.022 |
d | 65.684 | 0.000 |
e | 65.684 | 0.000 |
f | 92.082 | 0.000 |
g | 71.564 | 0.000 |
h | 74.667 | 0.000 |
i | 71.564 | 0.000 |
l | 65.684 | 0.000 |
m | 84.706 | 0.000 |
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 849.000 | 1.292 | 12 | 0.221 |
F2 | 1 233.000 | -2.103 | 12 | 0.057 | |
F3 | 2 460.000 | 1.990 | 12 | 0.070 | |
F4 | 3 358.000 | 0.922 | 11 | 0.376 | |
F5 | 4 980.000 | -1.063 | 9 | 0.316 | |
[i] | F1 | 849.000 | 1.292 | 12 | 0.221 |
F2 | 1 233.000 | -2.103 | 12 | 0.057 | |
F3 | 2 460.000 | 1.990 | 12 | 0.070 | |
F4 | 3 358.000 | 0.922 | 11 | 0.376 | |
F5 | 4 980.000 | -1.063 | 9 | 0.316 | |
[u] | F1 | 349.000 | -0.578 | 12 | 0.574 |
F2 | 847.000 | 0.772 | 12 | 0.455 | |
F3 | 2 268.000 | -1.787 | 10 | 0.104 | |
F4 | 3 112.000 | -0.694 | 11 | 0.502 | |
F5 | 3 837.000 | -1.077 | 9 | 0.309 |
Tab.8 One-sample t-test results of formants of vowel of volunteer No.1
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 849.000 | 1.292 | 12 | 0.221 |
F2 | 1 233.000 | -2.103 | 12 | 0.057 | |
F3 | 2 460.000 | 1.990 | 12 | 0.070 | |
F4 | 3 358.000 | 0.922 | 11 | 0.376 | |
F5 | 4 980.000 | -1.063 | 9 | 0.316 | |
[i] | F1 | 849.000 | 1.292 | 12 | 0.221 |
F2 | 1 233.000 | -2.103 | 12 | 0.057 | |
F3 | 2 460.000 | 1.990 | 12 | 0.070 | |
F4 | 3 358.000 | 0.922 | 11 | 0.376 | |
F5 | 4 980.000 | -1.063 | 9 | 0.316 | |
[u] | F1 | 349.000 | -0.578 | 12 | 0.574 |
F2 | 847.000 | 0.772 | 12 | 0.455 | |
F3 | 2 268.000 | -1.787 | 10 | 0.104 | |
F4 | 3 112.000 | -0.694 | 11 | 0.502 | |
F5 | 3 837.000 | -1.077 | 9 | 0.309 |
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 720.000 | 1.069 | 12 | 0.306 |
F2 | 1 220.000 | 1.843 | 12 | 0.090 | |
F3 | 2 506.000 | 1.566 | 10 | 0.148 | |
F4 | 3 529.000 | -1.525 | 10 | 0.158 | |
F5 | 4 536.000 | -0.687 | 9 | 0.510 | |
[i] | F1 | 411.000 | 0.097 | 12 | 0.925 |
F2 | 2 201.000 | 0.000 | 12 | 1.000 | |
F3 | 2 905.000 | 0.960 | 12 | 0.356 | |
F4 | 3 499.000 | -1.258 | 11 | 0.235 | |
F5 | 4 550.000 | -1.574 | 9 | 0.150 | |
[u] | F1 | 420.000 | 1.711 | 12 | 0.113 |
F2 | 890.000 | -1.526 | 12 | 0.153 | |
F3 | 2 465.000 | -0.719 | 9 | 0.490 | |
F4 | 3 031.000 | -1.536 | 9 | 0.159 | |
F5 | 3 646.000 | 0.810 | 9 | 0.439 |
Tab.9 One-sample t-test results of formants of vowel of volunteer No.4
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 720.000 | 1.069 | 12 | 0.306 |
F2 | 1 220.000 | 1.843 | 12 | 0.090 | |
F3 | 2 506.000 | 1.566 | 10 | 0.148 | |
F4 | 3 529.000 | -1.525 | 10 | 0.158 | |
F5 | 4 536.000 | -0.687 | 9 | 0.510 | |
[i] | F1 | 411.000 | 0.097 | 12 | 0.925 |
F2 | 2 201.000 | 0.000 | 12 | 1.000 | |
F3 | 2 905.000 | 0.960 | 12 | 0.356 | |
F4 | 3 499.000 | -1.258 | 11 | 0.235 | |
F5 | 4 550.000 | -1.574 | 9 | 0.150 | |
[u] | F1 | 420.000 | 1.711 | 12 | 0.113 |
F2 | 890.000 | -1.526 | 12 | 0.153 | |
F3 | 2 465.000 | -0.719 | 9 | 0.490 | |
F4 | 3 031.000 | -1.536 | 9 | 0.159 | |
F5 | 3 646.000 | 0.810 | 9 | 0.439 |
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 812.000 | 1.979 | 12 | 0.071 |
F2 | 1 420.000 | -1.346 | 12 | 0.203 | |
F3 | 3 138.000 | -0.021 | 11 | 0.984 | |
F4 | 4 163.000 | 0.306 | 9 | 0.766 | |
F5 | 5 073.000 | 0.621 | 9 | 0.550 | |
[i] | F1 | 433.000 | 0.106 | 12 | 0.918 |
F2 | 2 682.000 | -1.486 | 11 | 0.165 | |
F3 | 3 355.000 | -0.857 | 11 | 0.410 | |
F4 | 4 181.000 | 0.633 | 9 | 0.542 | |
F5 | 5 012.000 | 0.519 | 9 | 0.616 | |
[u] | F1 | 242.000 | 0.797 | 12 | 0.441 |
F2 | 563.000 | 1.391 | 12 | 0.189 | |
F3 | 3 047.000 | -1.086 | 12 | 0.299 | |
F4 | 3 822.000 | 0.232 | 9 | 0.822 | |
F5 | 4 340.000 | 0.628 | 9 | 0.546 |
Tab.10 One-sample t-test results of formants of vowel of volunteer No.7
元音 | 共振峰 | 检验值 | t | 自由度 | Sig.(双尾) |
---|---|---|---|---|---|
[a] | F1 | 812.000 | 1.979 | 12 | 0.071 |
F2 | 1 420.000 | -1.346 | 12 | 0.203 | |
F3 | 3 138.000 | -0.021 | 11 | 0.984 | |
F4 | 4 163.000 | 0.306 | 9 | 0.766 | |
F5 | 5 073.000 | 0.621 | 9 | 0.550 | |
[i] | F1 | 433.000 | 0.106 | 12 | 0.918 |
F2 | 2 682.000 | -1.486 | 11 | 0.165 | |
F3 | 3 355.000 | -0.857 | 11 | 0.410 | |
F4 | 4 181.000 | 0.633 | 9 | 0.542 | |
F5 | 5 012.000 | 0.519 | 9 | 0.616 | |
[u] | F1 | 242.000 | 0.797 | 12 | 0.441 |
F2 | 563.000 | 1.391 | 12 | 0.189 | |
F3 | 3 047.000 | -1.086 | 12 | 0.299 | |
F4 | 3 822.000 | 0.232 | 9 | 0.822 | |
F5 | 4 340.000 | 0.628 | 9 | 0.546 |
1 | 王英利,李敬阳,曹洪林. 声纹鉴定技术综述[J]. 警察技术, 2012(4):54-56. |
WANG Y L, LI J Y, CAO H L. Overview of voiceprint identification technique[J]. Police Technology, 2012(4):54-56. | |
2 | 王英利. 声纹鉴定技术[M]. 北京:群众出版社, 2013: 1-6, 55. 10.25103/jestr.062.17 |
WANG Y L. Voiceprint Identification Technology[M]. Beijing: Qunzhong Press, 2013: 1-6, 55. 10.25103/jestr.062.17 | |
3 | 樊昌信,曹丽娜. 通信原理[M]. 7版. 北京:国防工业出版社, 2012: 63. |
FAN C X, CAO L N. Principle of Communication[M]. 7th ed. Beijing: National Defense Industry Press, 2012: 63. | |
4 | 樊昌信,张甫翊,徐炳祥,等. 通信原理[M]. 5版. 北京:国防工业出版社, 2001: 34. |
FAN C X, ZHANG F Y, XU B X, et al. Principle of Communication[M]. 5th ed. Beijing: National Defense Industry Press, 2001: 34. | |
5 | 杨俊杰,李红明,岳玮,等. 通信信道及通信设备对语音共振峰特性的影响[J]. 山西警官高等专科学校学报, 2010, 18(1):78-80. 10.3969/j.issn.1671-685X.2010.01.019 |
YANG J J, LI H M, YUE W, et al. The Influence of the communication channels and communication equipment to voice formant frequency[J]. Journal of Shanxi Police Academy, 2010, 18(1):78-80. 10.3969/j.issn.1671-685X.2010.01.019 | |
6 | 邓宗权,邱立欣. 传统录音机和数码录音笔在信道中的差异[J]. 湖南警察学院学报, 2011, 23(6):120-124. 10.3969/j.issn.2095-1140.2011.06.026 |
DENG Z Q, QIU L X. The differences in transmission channels of traditional tape recorders and digital recorders[J]. Journal of Hunan Police Academy, 2011, 23(6):120-124. 10.3969/j.issn.2095-1140.2011.06.026 | |
7 | 张红兵.信道差异对语音鉴定影响的实验研究[C]// 第九届中国语音学学术会议论文集. 天津:出版者不详,2010:729-732. |
ZHANG H B. Experimental study on the influence of channel differences on speech recognition[C]// Proceedings of the 9th Phonetics Academic Conference of China.Tianjin:[s.n.],2010:729-732. | |
8 | 王丹,刘景天,张阳. 信道差异语音的特征变异分析研究[J]. 光电技术应用, 2019, 34(2):34-39. 10.3969/j.issn.1673-1255.2019.02.007 |
WANG D, LIU J T, ZHANG Y. Research on characteristic variation analysis of channel difference speech[J]. Electro-Optic Technology Application, 2019, 34(2):34-39. 10.3969/j.issn.1673-1255.2019.02.007 | |
9 | 张晓,孔华锋,王海燕,等. 网络语音同一性鉴定中的共振峰差异分析[J]. 计算机应用与软件, 2019, 36(3):187-191. 10.3969/j.issn.1000-386x.2019.03.034 |
ZHANG X, KONG H F, WANG H Y, et al. Difference analysis of formant in network voice identification[J]. Computer Applications and Software, 2019, 36(3):187-191. 10.3969/j.issn.1000-386x.2019.03.034 | |
10 | KAISER J, BOŘIL T. Impact of the GSM AMR codec on automatic vowel formant measurement in Praat and VoiceSauce[C]// Proceedings of the 41st International Conference on Telecommunications and Signal Processing. Piscataway: IEEE, 2018: 1-4. 10.1109/tsp.2018.8441185 |
11 | BARINOV A, KOVAL S, IGNATOV P, et al. Channel compensation for forensic speaker identification using inverse processing[C]// Proceedings of the 39th International Conference: Audio Forensics: Practices and Challenges. New York: Audio Engineering Society, 2010: 53-58. |
12 | VILLALBA J, CHEN N X, SNYDER D, et al. State-of-the-art speaker recognition for telephone and video speech: the JHU-MIT submission for NIST SRE18[C]// Proceedings of the Interspeech 2019. [S.l.]: International Speech Communication Association, 2019: 1488-1492. 10.21437/interspeech.2019-2713 |
13 | SADJADI S O, GREENBERG C, SINGER E, et al. The 2019 NIST speaker recognition evaluation CTS challenge[C]// Proceedings of the 2020 Speaker and Language Recognition Workshop. [S.l.]: International Speech Communication Association, 2020: 266-272. 10.21437/odyssey.2020-38 |
14 | 王莉,王晓笛,康锦涛,等. “人工嘴”在语音声学分析中的应用研究[J]. 刑事技术, 2019, 44(1):9-12. |
WANG L, WANG X D, KANG J T, et al. Mouth simulator in acoustic analysis[J]. Forensic Science and Technology, 2019, 44(1):9-12. | |
15 | 中华人民共和国公安部. 法庭科学语音同一认定技术规范: [S]. 北京:中国标准出版社, 2017. 10.3969/j.issn.1006-902X.2011.02.001 |
The Ministry of Public Security of the People’s Republic of China. Specifications for voice identification in Forensics: [S]. Beijing: Standards Press of China, 2017. 10.3969/j.issn.1006-902X.2011.02.001 |
[1] | Yeheng LI, Guangsheng LUO, Qianmin SU. Logo detection algorithm based on improved YOLOv5 [J]. Journal of Computer Applications, 2024, 44(8): 2580-2587. |
[2] | Tong CHEN, Fengyu YANG, Yu XIONG, Hong YAN, Fuxing QIU. Construction method of voiceprint library based on multi-scale frequency-channel attention fusion [J]. Journal of Computer Applications, 2024, 44(8): 2407-2413. |
[3] | Fang LEI, Yongcai NIU. Channel estimation method for low earth orbit satellite MIMO-OTFS system based on improved generalized orthogonal matching pursuit [J]. Journal of Computer Applications, 2024, 44(8): 2514-2520. |
[4] | Chenqian LI, Jun LIU. Ultrasound carotid plaque segmentation method based on semi-supervision and multi-scale cascaded attention [J]. Journal of Computer Applications, 2024, 44(8): 2604-2610. |
[5] | Shangbin MO, Wenjun WANG, Ling DONG, Shengxiang GAO, Zhengtao YU. Single-channel speech enhancement based on multi-channel information aggregation and collaborative decoding [J]. Journal of Computer Applications, 2024, 44(8): 2611-2617. |
[6] | Hao CHAO, Shuqi FENG, Yongli LIU. Convolutional recurrent neural network optimized by multiple context vectors in EEG-based emotion recognition [J]. Journal of Computer Applications, 2024, 44(7): 2041-2046. |
[7] | Yuan TANG, Yanping CHEN, Ying HU, Ruizhang HUANG, Yongbin QIN. Relation extraction model based on multi-scale hybrid attention convolutional neural networks [J]. Journal of Computer Applications, 2024, 44(7): 2011-2017. |
[8] | Zihao YAO, Yuanming LI, Ziqiang MA, Yang LI, Lianggen WEI. Multi-object cache side-channel attack detection model based on machine learning [J]. Journal of Computer Applications, 2024, 44(6): 1862-1871. |
[9] | Boyue WANG, Yingxiang LI, Jiandan ZHONG. Segmentation network for day and night ground-based cloud images based on improved Res-UNet [J]. Journal of Computer Applications, 2024, 44(4): 1310-1316. |
[10] | Xintong QIN, Zhengyu SONG, Tianwei HOU, Feiyue WANG, Xin SUN, Wei LI. Channel access and resource allocation algorithm for adaptive p-persistent mobile ad hoc network [J]. Journal of Computer Applications, 2024, 44(3): 863-868. |
[11] | Weipeng JING, Qingxin XIAO, Hui LUO. Channel compensation algorithm for speaker recognition based on probabilistic spherical discriminant analysis [J]. Journal of Computer Applications, 2024, 44(2): 556-562. |
[12] | Fengtao HE, Binghui WANG, Bin ZHANG, Yi YANG, Yibo FENG. Multi-parameter channel transmission performance evaluation method with improved TCP/IP frame structure [J]. Journal of Computer Applications, 2024, 44(11): 3540-3547. |
[13] | Wen ZHOU, Yuzhang CHEN, Zhiyuan WEN, Shiqi WANG. Fish image classification based on positional overlapping patch embedding and multi-scale channel interactive attention [J]. Journal of Computer Applications, 2024, 44(10): 3209-3216. |
[14] | Sihang CHEN, Aiwen JIANG, Zhaoyang CUI, Mingwen WANG. Multi-channel multi-step integration model for generative visual dialogue [J]. Journal of Computer Applications, 2024, 44(1): 39-46. |
[15] | Mengmeng CHEN, Zhiwei QIAO. Sparse reconstruction of CT images based on Uformer with fused channel attention [J]. Journal of Computer Applications, 2023, 43(9): 2948-2954. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||