Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1934 - 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)
(57,058)
0 57,058
2 ➡️
(Org: 2)
(33,505)
0.07 33,505
3 ➡️
(Org: 3)
(29,239)
- 29,239
4 📈
(Org: 7)
(28,235)
0.31 28,235
5 📉
(Org: 4)
(22,874)
0 22,874
6 📉
(Org: 5)
(21,323)
0 21,323
7 📉
(Org: 6)
(20,844)
- 20,844
8 ➡️
(Org: 8)
(15,385)
0.02 15,385
9 ➡️
(Org: 9)
(14,614)
0.04 14,614
10 ➡️
(Org: 10)
(13,641)
0.01 13,641
11 📈
(Org: 14)
(13,159)
0.22 13,159
12 📉
(Org: 11)
(11,803)
0.01 11,803
13 📉
(Org: 12)
(11,468)
0 11,468
14 📉
(Org: 13)
(10,597)
0 10,597
15 📈
(Org: 42)
(10,308)
0.52 10,308
16 📉
(Org: 15)
(10,018)
0 10,018
17 📉
(Org: 16)
(9,872)
0.02 9,872
18 📉
(Org: 17)
(9,770)
0.04 9,770
19 ➡️
(Org: 19)
(9,579)
0.04 9,579
20 📉
(Org: 18)
(9,523)
0.02 9,523
21 📉
(Org: 20)
(8,496)
0.01 8,496
22 📉
(Org: 21)
(8,408)
0.04 8,408
23 ➡️
(Org: 23)
(8,240)
0.04 8,240
24 📉
(Org: 22)
(7,956)
0.01 7,956
25 📉
(Org: 24)
(7,830)
0.01 7,830
26 📉
(Org: 25)
(7,784)
- 7,784
27 📉
(Org: 26)
(7,689)
- 7,689
28 📉
(Org: 27)
(7,610)
0 7,610
29 📉
(Org: 28)
(7,316)
0.02 7,316
30 📉
(Org: 29)
(7,112)
0.02 7,112
31 📈
(Org: 49)
(6,869)
0.37 6,869
32 📉
(Org: 30)
(6,824)
0 6,824
33 📉
(Org: 31)
(6,680)
- 6,680
34 📉
(Org: 32)
(6,641)
- 6,641
35 📉
(Org: 33)
(6,559)
0.01 6,559
36 📉
(Org: 34)
(6,376)
0.01 6,376
37 📉
(Org: 36)
(6,223)
0.03 6,223
38 📉
(Org: 35)
(6,180)
- 6,180
39 📉
(Org: 37)
(5,583)
- 5,583
40 📈
(Org: 67)
(5,445)
0.34 5,445
41 📈
(Org: 44)
(5,398)
0.13 5,398
42 📉
(Org: 39)
(5,187)
0.04 5,187
43 📉
(Org: 41)
(5,171)
0.04 5,171
44 📉
(Org: 43)
(5,067)
0.05 5,067
45 📉
(Org: 38)
(5,017)
- 5,017
46 📉
(Org: 40)
(4,980)
0 4,980
47 📈
(Org: 48)
(4,481)
0.03 4,481
48 📉
(Org: 46)
(4,387)
- 4,387
49 📉
(Org: 47)
(4,379)
0 4,379
50 📈
(Org: 62)
(4,304)
0.13 4,304
51 📈
(Org: 56)
(4,052)
0.07 4,052
52 ➡️
(Org: 52)
(4,020)
0.01 4,020
53 ➡️
(Org: 53)
(4,012)
0.02 4,012
54 📈
(Org: 57)
(3,992)
0.06 3,992
55 📉
(Org: 51)
(3,991)
- 3,991
56 📉
(Org: 54)
(3,966)
0.02 3,966
57 📈
(Org: 77)
(3,933)
0.19 3,933
58 📈
(Org: 80)
(3,898)
0.22 3,898
59 📉
(Org: 55)
(3,809)
- 3,809
60 📈
(Org: 63)
(3,798)
0.03 3,798
61 📉
(Org: 58)
(3,791)
0.01 3,791
62 📉
(Org: 61)
(3,762)
0.01 3,762
63 📉
(Org: 60)
(3,759)
0 3,759
64 📉
(Org: 59)
(3,750)
- 3,750
65 📈
(Org: 69)
(3,701)
0.03 3,701
66 ➡️
(Org: 66)
(3,674)
0.02 3,674
67 📉
(Org: 64)
(3,662)
- 3,662
68 📉
(Org: 65)
(3,646)
- 3,646
69 📉
(Org: 68)
(3,588)
- 3,588
70 📈
(Org: 75)
(3,522)
0.08 3,522
71 📉
(Org: 70)
(3,500)
0.01 3,500
72 📉
(Org: 71)
(3,469)
0.01 3,469
73 📉
(Org: 72)
(3,440)
0 3,440
74 ➡️
(Org: 74)
(3,399)
0.04 3,399
75 📉
(Org: 73)
(3,337)
0.01 3,337
76 📈
(Org: 82)
(3,335)
0.11 3,335
77 📈
(Org: 84)
(3,227)
0.09 3,227
78 📉
(Org: 76)
(3,222)
- 3,222
79 📈
(Org: 106)
(3,212)
0.29 3,212
80 📈
(Org: 83)
(3,191)
0.07 3,191
81 📉
(Org: 78)
(3,178)
- 3,178
82 📈
(Org: 97)
(3,121)
0.22 3,121
83 📉
(Org: 79)
(3,116)
0.01 3,116
84 📈
(Org: 138)
(3,026)
0.51 3,026
85 📈
(Org: 111)
(3,025)
0.3 3,025
86 📉
(Org: 81)
(3,012)
- 3,012
87 📉
(Org: 85)
(2,964)
0.01 2,964
88 📉
(Org: 86)
(2,892)
0 2,892
89 📉
(Org: 87)
(2,840)
0.01 2,840
90 ➡️
(Org: 90)
(2,795)
0.07 2,795
91 📉
(Org: 88)
(2,786)
- 2,786
92 ➡️
(Org: 92)
(2,758)
0.07 2,758
93 📈
(Org: 96)
(2,688)
0.09 2,688
94 📉
(Org: 93)
(2,618)
0.03 2,618
95 📈
(Org: 110)
(2,592)
0.16 2,592
96 📉
(Org: 91)
(2,578)
- 2,578
97 📉
(Org: 95)
(2,489)
0.01 2,489
98 ➡️
(Org: 98)
(2,484)
0.03 2,484
99 📉
(Org: 94)
(2,459)
- 2,459
100 📈
(Org: 116)
(2,423)
0.18 2,423