Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1992 - Combined Name Rankings

About Distortion Index

The Distortion Index shows how much the ranking might be skewed by alternative spellings of the same pronunciation. A higher index (closer to 1.0) means the main name represents a smaller portion of the total, indicating the ranking could be misleading. A lower index (closer to 0.0) means the main name dominates, making the ranking more accurate.

Low Distortion (0.07): Jayden (1,000) + Zayden (50) + Jaden (30) = Main name dominates
High Distortion (0.91): Jayden (100) + Zayden (800) + Jaden (200) = Alternative spellings dominate
Distortion Index Color Guide:
0.0-0.29 Low Distortion (Green) - Main name dominates
0.3-0.69 Medium Distortion (Orange) - Moderate alternative spellings
0.7-1.0 High Distortion (Red) - Alternative spellings dominate
Rank Adjustment Explanation:

Adjusted Rank: The primary rank shown reflects the combined count of all similar pronunciation names, providing a more accurate representation of the name's true popularity. Original Rank: The rank in parentheses shows the original ranking based on the main name only, before grouping similar pronunciations.

Rank Change Indicators:
📈 Rank improved (moved up)
📉 Rank declined (moved down)
➡️ Rank unchanged

Advanced Pronunciation Algorithm

We've developed a revolutionary pronunciation comparison algorithm that intelligently groups baby names with similar sounds and pronunciations. Our sophisticated system automatically corrects common typos and misspellings, ensuring accurate name grouping based on phonetic similarity rather than just spelling.

This cutting-edge algorithm uses advanced phonetic analysis to identify names that sound alike but may have different spellings, providing you with the most comprehensive and accurate baby name rankings by pronunciation. 💡 Understanding the Distortion Index is crucial for interpreting these results accurately. While our algorithm is highly accurate, if you notice any grouping errors, please let us know and we'll promptly resolve them.

🔍 Intelligent phonetic analysis and grouping
✏️ Automatic typo correction and misspelling detection
🎯 Accurate pronunciation-based name categorization

Girl Names

Ranking Name Distortion Index Count
1 ➡️
(Org: 1)
(41,174)
0.07 41,174
2 ➡️
(Org: 2)
(39,159)
0.02 39,159
3 📈
(Org: 5)
(33,152)
0.26 33,152
4 ➡️
(Org: 4)
(27,349)
0.09 27,349
5 📈
(Org: 42)
(25,739)
0.71 25,739
6 📉
(Org: 3)
(25,064)
0 25,064
7 📉
(Org: 6)
(24,475)
0 24,475
8 📈
(Org: 27)
(23,147)
0.52 23,147
9 📉
(Org: 7)
(22,836)
0.04 22,836
10 📉
(Org: 8)
(22,021)
0.11 22,021
11 📈
(Org: 15)
(21,427)
0.25 21,427
12 📉
(Org: 9)
(19,865)
0.04 19,865
13 📈
(Org: 16)
(19,219)
0.18 19,219
14 📉
(Org: 10)
(18,738)
0.05 18,738
15 📉
(Org: 14)
(18,568)
0.12 18,568
16 📉
(Org: 11)
(18,412)
0.03 18,412
17 📉
(Org: 12)
(17,704)
0.03 17,704
18 📉
(Org: 13)
(17,167)
0.04 17,167
19 📈
(Org: 53)
(16,093)
0.61 16,093
20 ➡️
(Org: 20)
(16,039)
0.18 16,039
21 📉
(Org: 17)
(16,016)
0.07 16,016
22 📈
(Org: 33)
(15,098)
0.37 15,098
23 📉
(Org: 18)
(14,959)
0.06 14,959
24 📉
(Org: 21)
(14,853)
0.15 14,853
25 📉
(Org: 23)
(14,354)
0.18 14,354
26 📉
(Org: 19)
(13,947)
0 13,947
27 📈
(Org: 43)
(13,307)
0.45 13,307
28 📉
(Org: 25)
(12,462)
0.08 12,462
29 📉
(Org: 26)
(12,443)
0.08 12,443
30 📈
(Org: 44)
(12,311)
0.42 12,311
31 📉
(Org: 28)
(12,294)
0.15 12,294
31 📈
(Org: 56)
(12,294)
0.51 12,294
33 📉
(Org: 24)
(12,228)
0.04 12,228
34 📉
(Org: 22)
(11,969)
0.01 11,969
35 📉
(Org: 30)
(11,914)
0.15 11,914
36 📈
(Org: 45)
(11,844)
0.4 11,844
37 📉
(Org: 32)
(10,763)
0.1 10,763
38 📉
(Org: 29)
(10,687)
0.04 10,687
39 📉
(Org: 34)
(10,559)
0.11 10,559
40 📈
(Org: 50)
(10,496)
0.37 10,496
41 📈
(Org: 47)
(10,316)
0.32 10,316
42 📈
(Org: 48)
(10,184)
0.32 10,184
43 📉
(Org: 31)
(9,724)
- 9,724
44 📉
(Org: 35)
(9,668)
0.08 9,668
45 📈
(Org: 52)
(8,578)
0.26 8,578
46 📈
(Org: 68)
(8,569)
0.41 8,569
47 📈
(Org: 76)
(8,562)
0.45 8,562
48 📉
(Org: 38)
(8,538)
0.03 8,538
48 📉
(Org: 36)
(8,538)
0.01 8,538
50 📉
(Org: 40)
(8,136)
0.02 8,136
51 📉
(Org: 39)
(8,024)
- 8,024
52 📉
(Org: 41)
(7,987)
0.02 7,987
53 📉
(Org: 46)
(7,411)
0.05 7,411
54 📈
(Org: 57)
(7,350)
0.2 7,350
55 📉
(Org: 49)
(6,894)
0.01 6,894
56 📉
(Org: 54)
(6,834)
0.11 6,834
57 📈
(Org: 134)
(6,610)
0.63 6,610
58 📈
(Org: 61)
(6,461)
0.14 6,461
59 📈
(Org: 72)
(6,424)
0.24 6,424
60 📉
(Org: 55)
(6,402)
0.05 6,402
61 📉
(Org: 51)
(6,340)
- 6,340
62 📈
(Org: 109)
(6,093)
0.51 6,093
63 📉
(Org: 59)
(6,083)
0.05 6,083
64 📈
(Org: 71)
(6,008)
0.18 6,008
65 📈
(Org: 75)
(5,981)
0.21 5,981
66 📉
(Org: 58)
(5,840)
0 5,840
67 📉
(Org: 63)
(5,713)
0.06 5,713
68 📉
(Org: 67)
(5,655)
0.1 5,655
69 📉
(Org: 64)
(5,445)
0.03 5,445
70 📉
(Org: 66)
(5,380)
0.02 5,380
71 📈
(Org: 110)
(5,360)
0.45 5,360
72 📈
(Org: 174)
(5,341)
0.67 5,341
73 📉
(Org: 69)
(5,130)
0.01 5,130
74 📈
(Org: 87)
(5,072)
0.22 5,072
75 📉
(Org: 70)
(5,060)
0.01 5,060
76 📉
(Org: 73)
(4,951)
0.03 4,951
77 ➡️
(Org: 77)
(4,854)
0.05 4,854
78 📈
(Org: 83)
(4,709)
0.12 4,709
79 📈
(Org: 81)
(4,559)
0.07 4,559
80 📈
(Org: 129)
(4,440)
0.41 4,440
81 📈
(Org: 84)
(4,390)
0.08 4,390
82 📈
(Org: 114)
(4,312)
0.32 4,312
83 📈
(Org: 125)
(4,238)
0.37 4,238
84 📈
(Org: 85)
(4,162)
0.04 4,162
85 📈
(Org: 86)
(4,098)
0.03 4,098
86 📈
(Org: 96)
(4,054)
0.15 4,054
87 📈
(Org: 88)
(4,013)
0.06 4,013
88 📈
(Org: 99)
(3,970)
0.16 3,970
89 ➡️
(Org: 89)
(3,928)
0.06 3,928
90 📈
(Org: 92)
(3,828)
0.07 3,828
91 📈
(Org: 305)
(3,764)
0.76 3,764
91 📈
(Org: 132)
(3,764)
0.33 3,764
93 📈
(Org: 124)
(3,699)
0.27 3,699
94 📈
(Org: 130)
(3,687)
0.29 3,687
95 📈
(Org: 138)
(3,662)
0.38 3,662
96 📉
(Org: 91)
(3,629)
0.01 3,629
97 📉
(Org: 94)
(3,616)
0.05 3,616
98 📉
(Org: 97)
(3,600)
0.06 3,600
99 📉
(Org: 98)
(3,523)
0.05 3,523
99 📉
(Org: 95)
(3,523)
0.02 3,523