Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1996 - 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: 4)
(27,419)
0.23 27,419
2 📉
(Org: 1)
(26,670)
0.06 26,670
3 📈
(Org: 40)
(25,824)
0.72 25,824
4 📉
(Org: 3)
(25,823)
0.08 25,823
5 📉
(Org: 2)
(24,772)
0.02 24,772
6 📉
(Org: 5)
(20,579)
0 20,579
7 📉
(Org: 6)
(20,307)
0.06 20,307
8 📉
(Org: 7)
(20,018)
0.07 20,018
9 ➡️
(Org: 9)
(19,084)
0.16 19,084
10 📈
(Org: 17)
(18,830)
0.37 18,830
11 📈
(Org: 30)
(18,608)
0.51 18,608
12 📈
(Org: 31)
(17,939)
0.51 17,939
13 📉
(Org: 8)
(17,040)
0.03 17,040
14 📉
(Org: 10)
(16,839)
0.05 16,839
15 📉
(Org: 11)
(16,106)
0.05 16,106
16 📉
(Org: 12)
(15,390)
0.04 15,390
17 📉
(Org: 14)
(14,942)
0.08 14,942
18 📉
(Org: 15)
(14,121)
0.05 14,121
19 📉
(Org: 13)
(13,993)
0 13,993
20 📈
(Org: 24)
(13,576)
0.22 13,576
21 ➡️
(Org: 21)
(13,257)
0.14 13,257
22 📉
(Org: 20)
(13,109)
0.11 13,109
23 📈
(Org: 37)
(13,082)
0.42 13,082
24 📉
(Org: 16)
(12,949)
0.03 12,949
25 📉
(Org: 23)
(12,819)
0.14 12,819
26 📉
(Org: 22)
(12,383)
0.1 12,383
27 📉
(Org: 19)
(12,247)
0.04 12,247
28 📉
(Org: 18)
(11,944)
0.01 11,944
29 📉
(Org: 28)
(11,828)
0.18 11,828
30 📈
(Org: 70)
(10,685)
0.55 10,685
31 📈
(Org: 38)
(10,594)
0.3 10,594
32 📉
(Org: 25)
(10,545)
0.02 10,545
33 📉
(Org: 26)
(10,347)
0.03 10,347
34 📈
(Org: 36)
(9,975)
0.23 9,975
35 📉
(Org: 29)
(9,805)
0.05 9,805
36 📉
(Org: 27)
(9,803)
0 9,803
37 📈
(Org: 57)
(9,404)
0.38 9,404
38 📈
(Org: 39)
(9,340)
0.22 9,340
39 📉
(Org: 32)
(8,959)
0.04 8,959
40 📉
(Org: 35)
(8,780)
0.09 8,780
41 📈
(Org: 43)
(8,753)
0.2 8,753
42 📉
(Org: 33)
(8,627)
0.01 8,627
43 📉
(Org: 34)
(8,194)
0.01 8,194
44 📈
(Org: 55)
(8,174)
0.28 8,174
45 📈
(Org: 79)
(8,069)
0.45 8,069
46 📈
(Org: 56)
(8,013)
0.27 8,013
47 📈
(Org: 75)
(7,956)
0.42 7,956
48 📈
(Org: 62)
(7,920)
0.31 7,920
49 📈
(Org: 59)
(7,872)
0.27 7,872
50 📉
(Org: 41)
(7,764)
0.08 7,764
51 📉
(Org: 46)
(7,715)
0.13 7,715
52 📉
(Org: 42)
(7,529)
0.05 7,529
53 📈
(Org: 69)
(7,518)
0.35 7,518
54 📈
(Org: 126)
(7,395)
0.66 7,395
55 📉
(Org: 47)
(7,102)
0.07 7,102
56 📉
(Org: 52)
(7,070)
0.13 7,070
57 📉
(Org: 45)
(7,035)
0.04 7,035
58 📉
(Org: 44)
(7,026)
0.01 7,026
59 📈
(Org: 110)
(6,947)
0.6 6,947
60 📈
(Org: 73)
(6,686)
0.29 6,686
61 📉
(Org: 49)
(6,619)
0.05 6,619
62 📉
(Org: 51)
(6,570)
0.05 6,570
63 📉
(Org: 48)
(6,371)
0.01 6,371
64 📉
(Org: 54)
(6,285)
0.06 6,285
65 📈
(Org: 89)
(6,232)
0.36 6,232
66 📉
(Org: 53)
(6,207)
0.01 6,207
67 📈
(Org: 85)
(6,186)
0.32 6,186
68 📉
(Org: 67)
(6,153)
0.2 6,153
69 📉
(Org: 60)
(6,142)
0.06 6,142
70 📈
(Org: 92)
(6,092)
0.38 6,092
71 📉
(Org: 58)
(5,889)
0.02 5,889
72 📉
(Org: 61)
(5,671)
- 5,671
73 📉
(Org: 65)
(5,485)
0.03 5,485
74 📉
(Org: 66)
(5,365)
0.03 5,365
75 📈
(Org: 86)
(5,208)
0.21 5,208
76 📈
(Org: 121)
(5,154)
0.51 5,154
77 📈
(Org: 111)
(5,120)
0.45 5,120
78 📉
(Org: 68)
(5,119)
0.05 5,119
79 📈
(Org: 83)
(5,092)
0.16 5,092
80 📈
(Org: 102)
(5,067)
0.37 5,067
81 📉
(Org: 74)
(4,904)
0.04 4,904
82 📈
(Org: 91)
(4,901)
0.21 4,901
83 📉
(Org: 76)
(4,866)
0.06 4,866
84 📉
(Org: 81)
(4,786)
0.1 4,786
85 📈
(Org: 131)
(4,760)
0.49 4,760
86 📉
(Org: 71)
(4,759)
- 4,759
87 📉
(Org: 77)
(4,730)
0.04 4,730
88 📉
(Org: 82)
(4,612)
0.06 4,612
89 📉
(Org: 78)
(4,492)
0.01 4,492
90 📈
(Org: 96)
(4,461)
0.19 4,461
91 📉
(Org: 80)
(4,387)
0.01 4,387
92 📈
(Org: 115)
(4,344)
0.37 4,344
93 📉
(Org: 88)
(4,067)
- 4,067
94 📈
(Org: 98)
(4,059)
0.18 4,059
95 📉
(Org: 90)
(3,901)
0.01 3,901
96 📈
(Org: 127)
(3,856)
0.35 3,856
97 📈
(Org: 99)
(3,821)
0.13 3,821
98 📉
(Org: 94)
(3,760)
0.01 3,760
99 📈
(Org: 161)
(3,687)
0.47 3,687
100 📈
(Org: 118)
(3,603)
0.26 3,603