Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1947 - 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)
(104,612)
0.05 104,612
2 ➡️
(Org: 2)
(72,183)
0.01 72,183
3 ➡️
(Org: 3)
(51,283)
0 51,283
4 ➡️
(Org: 4)
(48,810)
0 48,810
5 📈
(Org: 8)
(39,384)
0.19 39,384
6 ➡️
(Org: 6)
(37,764)
0.11 37,764
7 📉
(Org: 5)
(35,592)
0.02 35,592
8 📉
(Org: 7)
(32,810)
0.01 32,810
9 ➡️
(Org: 9)
(29,346)
0.03 29,346
10 ➡️
(Org: 10)
(23,960)
0.02 23,960
11 ➡️
(Org: 11)
(22,949)
0.04 22,949
12 ➡️
(Org: 12)
(22,082)
0 22,082
13 📈
(Org: 14)
(21,952)
0.04 21,952
14 📉
(Org: 13)
(21,948)
0.01 21,948
15 📈
(Org: 30)
(21,699)
0.48 21,699
16 📈
(Org: 17)
(21,128)
0.1 21,128
17 📉
(Org: 15)
(21,035)
0.01 21,035
18 📉
(Org: 16)
(20,345)
0.01 20,345
19 📈
(Org: 46)
(20,221)
0.61 20,221
20 📉
(Org: 18)
(17,775)
- 17,775
21 📉
(Org: 19)
(17,673)
0 17,673
22 📈
(Org: 24)
(16,100)
0.14 16,100
23 📉
(Org: 20)
(15,940)
0 15,940
24 📉
(Org: 21)
(15,830)
- 15,830
25 📉
(Org: 23)
(15,810)
0.04 15,810
26 📉
(Org: 22)
(15,409)
- 15,409
27 📉
(Org: 25)
(13,693)
0.02 13,693
28 📉
(Org: 26)
(12,790)
0 12,790
29 📉
(Org: 28)
(12,693)
0.02 12,693
30 📉
(Org: 27)
(12,626)
- 12,626
31 📉
(Org: 29)
(12,460)
0.05 12,460
32 📉
(Org: 31)
(11,284)
0.01 11,284
33 📉
(Org: 32)
(10,652)
- 10,652
34 📈
(Org: 49)
(10,585)
0.32 10,585
35 📉
(Org: 33)
(10,556)
0 10,556
36 ➡️
(Org: 36)
(10,547)
0.06 10,547
37 📉
(Org: 34)
(10,423)
0 10,423
37 📉
(Org: 35)
(10,423)
0.02 10,423
39 📈
(Org: 64)
(9,730)
0.41 9,730
40 📈
(Org: 45)
(9,706)
0.14 9,706
41 📉
(Org: 38)
(9,639)
0.07 9,639
42 📉
(Org: 37)
(9,494)
0.03 9,494
43 📉
(Org: 39)
(9,251)
0.03 9,251
44 📉
(Org: 42)
(9,166)
0.03 9,166
45 📉
(Org: 40)
(9,121)
0.02 9,121
46 📉
(Org: 41)
(8,894)
- 8,894
47 📉
(Org: 43)
(8,703)
0.01 8,703
48 📉
(Org: 44)
(8,502)
0 8,502
49 📈
(Org: 59)
(7,892)
0.24 7,892
50 📈
(Org: 91)
(7,863)
0.46 7,863
51 📉
(Org: 47)
(7,855)
0 7,855
52 📉
(Org: 48)
(7,622)
- 7,622
53 📈
(Org: 85)
(7,295)
0.4 7,295
54 📈
(Org: 75)
(7,227)
0.31 7,227
55 📉
(Org: 50)
(7,181)
0.02 7,181
56 📉
(Org: 51)
(6,951)
0.03 6,951
57 📈
(Org: 101)
(6,640)
0.42 6,640
58 📉
(Org: 52)
(6,461)
0.02 6,461
59 📈
(Org: 93)
(6,403)
0.34 6,403
60 📉
(Org: 57)
(6,204)
0.02 6,204
61 📉
(Org: 58)
(6,135)
0.02 6,135
62 📉
(Org: 54)
(6,121)
0 6,121
63 📉
(Org: 60)
(6,107)
0.02 6,107
64 📉
(Org: 62)
(5,947)
0.02 5,947
65 📈
(Org: 70)
(5,925)
0.11 5,925
66 📉
(Org: 61)
(5,905)
0.01 5,905
67 📉
(Org: 63)
(5,842)
0.02 5,842
68 📉
(Org: 67)
(5,782)
0.04 5,782
69 📈
(Org: 80)
(5,697)
0.2 5,697
70 📉
(Org: 66)
(5,677)
0 5,677
71 📉
(Org: 65)
(5,654)
- 5,654
72 📉
(Org: 71)
(5,610)
0.06 5,610
73 📈
(Org: 83)
(5,535)
0.2 5,535
74 ➡️
(Org: 74)
(5,435)
0.07 5,435
75 📉
(Org: 68)
(5,399)
0 5,399
76 📉
(Org: 72)
(5,343)
0.02 5,343
77 📉
(Org: 69)
(5,320)
0 5,320
78 📉
(Org: 73)
(5,095)
- 5,095
79 📉
(Org: 78)
(5,042)
0.05 5,042
80 📉
(Org: 79)
(4,738)
0.01 4,738
81 📈
(Org: 84)
(4,722)
0.07 4,722
82 📉
(Org: 81)
(4,485)
0 4,485
83 📉
(Org: 82)
(4,445)
0 4,445
84 📈
(Org: 86)
(4,426)
0.01 4,426
85 📈
(Org: 87)
(4,344)
- 4,344
86 📈
(Org: 88)
(4,339)
- 4,339
87 📈
(Org: 90)
(4,276)
0 4,276
88 📈
(Org: 92)
(4,238)
- 4,238
89 📈
(Org: 105)
(4,219)
0.18 4,219
90 📈
(Org: 94)
(4,194)
0 4,194
91 📈
(Org: 94)
(4,187)
- 4,187
92 📈
(Org: 97)
(4,185)
0.02 4,185
93 📈
(Org: 96)
(4,171)
0 4,171
94 📈
(Org: 98)
(4,165)
0.02 4,165
95 📈
(Org: 104)
(4,079)
0.14 4,079
96 📈
(Org: 99)
(4,056)
0 4,056
97 📈
(Org: 100)
(3,894)
- 3,894
98 📈
(Org: 103)
(3,758)
- 3,758
99 📈
(Org: 135)
(3,670)
0.38 3,670
100 📈
(Org: 125)
(3,604)
0.28 3,604