Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2012 - 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)
(30,330)
0.26 30,330
2 ➡️
(Org: 2)
(21,415)
0.02 21,415
3 ➡️
(Org: 3)
(19,823)
0.03 19,823
4 ➡️
(Org: 4)
(17,562)
0.01 17,562
5 ➡️
(Org: 5)
(15,899)
0.02 15,899
6 📈
(Org: 20)
(15,635)
0.52 15,635
7 📈
(Org: 11)
(14,967)
0.35 14,967
8 📉
(Org: 6)
(14,779)
0.08 14,779
9 📈
(Org: 15)
(13,831)
0.42 13,831
10 📉
(Org: 7)
(13,283)
0.04 13,283
11 📉
(Org: 8)
(12,707)
0.05 12,707
12 📉
(Org: 9)
(12,471)
0.08 12,471
13 📈
(Org: 16)
(11,969)
0.33 11,969
14 📈
(Org: 32)
(11,214)
0.47 11,214
15 📈
(Org: 34)
(10,772)
0.48 10,772
16 📉
(Org: 10)
(10,263)
0.05 10,263
17 ➡️
(Org: 17)
(10,019)
0.21 10,019
18 📈
(Org: 47)
(9,785)
0.51 9,785
19 📉
(Org: 14)
(9,458)
0.13 9,458
20 📉
(Org: 12)
(9,392)
0.02 9,392
21 📈
(Org: 29)
(9,364)
0.27 9,364
22 📈
(Org: 31)
(9,265)
0.32 9,265
23 📈
(Org: 25)
(9,186)
0.22 9,186
24 📈
(Org: 59)
(9,052)
0.54 9,052
25 📈
(Org: 67)
(9,045)
0.58 9,045
26 📈
(Org: 49)
(8,860)
0.47 8,860
27 📈
(Org: 36)
(8,845)
0.38 8,845
28 📈
(Org: 71)
(8,427)
0.55 8,427
29 📈
(Org: 118)
(8,416)
0.69 8,416
30 📉
(Org: 13)
(8,318)
- 8,318
31 📉
(Org: 22)
(8,207)
0.11 8,207
32 📈
(Org: 38)
(8,054)
0.33 8,054
33 ➡️
(Org: 33)
(7,960)
0.27 7,960
34 📈
(Org: 53)
(7,944)
0.44 7,944
35 📉
(Org: 27)
(7,704)
0.11 7,704
36 📈
(Org: 64)
(7,511)
0.47 7,511
37 📈
(Org: 42)
(7,500)
0.31 7,500
38 📉
(Org: 19)
(7,482)
- 7,482
39 📉
(Org: 21)
(7,438)
0.01 7,438
40 📉
(Org: 23)
(7,334)
0.01 7,334
41 📉
(Org: 24)
(7,199)
- 7,199
42 📉
(Org: 37)
(7,150)
0.23 7,150
43 📉
(Org: 28)
(7,032)
0.02 7,032
44 📉
(Org: 26)
(6,937)
- 6,937
45 📈
(Org: 48)
(6,842)
0.3 6,842
46 📈
(Org: 63)
(6,716)
0.41 6,716
47 📈
(Org: 143)
(6,693)
0.66 6,693
48 📈
(Org: 51)
(6,446)
0.28 6,446
49 📈
(Org: 285)
(6,283)
0.82 6,283
50 📉
(Org: 43)
(6,181)
0.16 6,181
51 📈
(Org: 101)
(5,981)
0.49 5,981
52 📉
(Org: 44)
(5,937)
0.14 5,937
53 📈
(Org: 81)
(5,687)
0.4 5,687
54 📉
(Org: 41)
(5,685)
0.07 5,685
55 📉
(Org: 35)
(5,669)
0.01 5,669
56 📈
(Org: 93)
(5,546)
0.42 5,546
57 📉
(Org: 45)
(5,503)
0.1 5,503
58 📉
(Org: 40)
(5,486)
0.02 5,486
59 📉
(Org: 39)
(5,416)
0 5,416
60 📈
(Org: 61)
(5,228)
0.23 5,228
61 📈
(Org: 126)
(5,172)
0.52 5,172
62 📉
(Org: 46)
(5,129)
0.05 5,129
63 📉
(Org: 50)
(5,068)
0.07 5,068
64 📉
(Org: 52)
(4,995)
0.08 4,995
65 📈
(Org: 117)
(4,792)
0.45 4,792
66 📉
(Org: 56)
(4,688)
0.08 4,688
67 📉
(Org: 54)
(4,473)
0.03 4,473
68 📉
(Org: 58)
(4,454)
0.05 4,454
69 📉
(Org: 57)
(4,414)
0.03 4,414
70 📈
(Org: 77)
(4,404)
0.21 4,404
71 📈
(Org: 108)
(4,400)
0.34 4,400
72 📈
(Org: 87)
(4,295)
0.22 4,295
73 📉
(Org: 69)
(4,279)
0.12 4,279
74 📈
(Org: 78)
(4,267)
0.19 4,267
75 📉
(Org: 70)
(4,230)
0.11 4,230
76 📈
(Org: 83)
(4,183)
0.19 4,183
77 📉
(Org: 66)
(4,154)
0.08 4,154
78 📈
(Org: 84)
(4,112)
0.18 4,112
79 📈
(Org: 214)
(4,046)
0.64 4,046
80 📉
(Org: 62)
(4,035)
0.01 4,035
80 📉
(Org: 65)
(4,035)
0.04 4,035
82 📈
(Org: 99)
(3,898)
0.22 3,898
83 📈
(Org: 85)
(3,891)
0.13 3,891
84 📉
(Org: 73)
(3,840)
0.06 3,840
85 📉
(Org: 72)
(3,816)
0.04 3,816
86 📉
(Org: 68)
(3,807)
0.01 3,807
87 📈
(Org: 90)
(3,806)
0.14 3,806
88 📈
(Org: 163)
(3,788)
0.49 3,788
89 📈
(Org: 148)
(3,706)
0.42 3,706
89 📉
(Org: 76)
(3,706)
0.06 3,706
91 📉
(Org: 75)
(3,676)
0.03 3,676
92 ➡️
(Org: 92)
(3,645)
0.11 3,645
93 📈
(Org: 417)
(3,644)
0.79 3,644
94 📈
(Org: 409)
(3,607)
0.79 3,607
95 📉
(Org: 79)
(3,606)
0.05 3,606
96 📈
(Org: 140)
(3,560)
0.36 3,560
97 📉
(Org: 88)
(3,540)
0.06 3,540
98 📉
(Org: 91)
(3,488)
0.07 3,488
99 📉
(Org: 82)
(3,475)
0.02 3,475
100 📈
(Org: 113)
(3,472)
0.22 3,472