Skip to content

Phonetic Name Matcher

Double Metaphone + Soundex computed in your browser: cluster names that sound alike, score similarity, and de-duplicate a pasted CSV column.

Phonetic codes (25 names)

8 multi-name clusters - 7 singletons
NameDM primaryDM secondarySoundexCluster
SmithSMA0SMATS530#1 (weak)
SmythSMA0SMATS530#1 (weak)
SchmidtXMATSKMAS530#2 (weak)
JonJANAANJ500#3
JohnJANAANJ500#3
CatherineKATAKATAC365#4
KatherineKATAKATAK365#4 (weak)
KathrynKA0RKATRK365#5 (weak)
XavierSAFASAFAX160#6
JavierJAFAAAFAJ160#7
ThompsonTAMPTAMPT512#8
TompsonTAMPTAMPT512#8
StephenSTAFSTAFS315#9
StefanSTAFSTAFS315#9
NguyenNKAANKAAN250#10
WinAANFANW500#3
WynnAANFANW500#3
PhilipFALAFALAP410#11
FilipFALAFALAF410#11
EllenALANALANE450#12
HelenHALAHALAH450#13
GrayKRAAKRAAG600#14
GreyKRAAKRAAG600#14
RogersRAKRRAJRR262#15
RodgersRAJRRAJRR326#15

Clusters

SMA0primary

Matched key: SMA0 - mean similarity 80%

  • SmithSMA0/SMAT - S530
  • SmythSMA0/SMAT - S530
PairLevenshtein %Jaro-Winkler %
Smith -  Smyth80.089.3
JANprimary

Matched key: JAN - mean similarity 38.9%

  • JonJAN/AAN - J500
  • JohnJAN/AAN - J500
  • WinAAN/FAN - W500
  • WynnAAN/FAN - W500
PairLevenshtein %Jaro-Winkler %
Jon -  John75.093.3
Jon -  Win33.355.6
Jon -  Wynn25.052.8
John -  Win25.052.8
John -  Wynn25.050.0
Win -  Wynn50.075.0
KATAprimary

Matched key: KATA - mean similarity 88.9%

  • CatherineKATA/KATA - C365
  • KatherineKATA/KATA - K365
PairLevenshtein %Jaro-Winkler %
Catherine -  Katherine88.992.6
TAMPprimary

Matched key: TAMP - mean similarity 87.5%

  • ThompsonTAMP/TAMP - T512
  • TompsonTAMP/TAMP - T512
PairLevenshtein %Jaro-Winkler %
Thompson -  Tompson87.596.3
STAFprimary

Matched key: STAF - mean similarity 57.1%

  • StephenSTAF/STAF - S315
  • StefanSTAF/STAF - S315
PairLevenshtein %Jaro-Winkler %
Stephen -  Stefan57.182.2
FALAprimary

Matched key: FALA - mean similarity 66.7%

  • PhilipFALA/FALA - P410
  • FilipFALA/FALA - F410
PairLevenshtein %Jaro-Winkler %
Philip -  Filip66.782.2
KRAAprimary

Matched key: KRAA - mean similarity 75%

  • GrayKRAA/KRAA - G600
  • GreyKRAA/KRAA - G600
PairLevenshtein %Jaro-Winkler %
Gray -  Grey75.086.7
RAKR -  RAJRcross

Matched key: RAKR -  RAJR - mean similarity 85.7%

  • RogersRAKR/RAJR - R262
  • RodgersRAJR/RAJR - R326
PairLevenshtein %Jaro-Winkler %
Rogers -  Rodgers85.796.2

Weaker matches - identical Soundex but different Double Metaphone keys:

  • Smith (S530) - DM SMA0
  • Smyth (S530) - DM SMA0
  • Schmidt (S530) - DM XMAT
  • Katherine (K365) - DM KATA
  • Kathryn (K365) - DM KA0R

Dedupe & export

No likely duplicates at 90% similarity. Lower the threshold to catch more.

25 of 25 records kept

Known-answer check

0/8 primary codes match the reference
NameReference (primary/secondary)This implementationNote
SmithSM0/XMTSMA0/SMATreference primary SM0
SmythSM0/XMTSMA0/SMATreference primary SM0
CatherineK0RN/KTRNKATA/KATAreference primary K0RN
KatherineK0RN/KTRNKATA/KATAreference primary K0RN
JonJN/ANJAN/AANreference primary JN
JohnJN/ANJAN/AANreference primary JN
XavierSF/SFRSAFA/SAFAinitial X splits S / SF
ThompsonTMSN/TMSNTAMP/TAMPGreek-th path, not 0

About this tool

Double Metaphone is Lawrence Philips' 2000 phonetic algorithm. It encodes how a name sounds rather than how it is spelled, and returns two codes: a primary for the most likely pronunciation and a secondary for a plausible alternative - which is why international names match so much better with it than with plain Soundex. Smith and Smyth both reduce to SM0 because the "th" digraph maps to 0 (the theta sound) and "i" versus "y" collapse to the same vowel code, so the two spellings cluster together. This implementation follows Philips' published C reference, with the initial "X" special case that yields SF/SFR for Xavier.

Soundex is computed alongside using the American Soundex rules (first letter kept, vowels and Y dropped while H and W stay transparent, adjacent duplicate codes collapsed, padded to four characters). Groups whose Soundex matches but whose Double Metaphone codes differ are flagged as weaker matches instead of being merged. Similarity scores use Levenshtein distance normalised to a percentage, plus Jaro-Winkler.

All of it - parsing, phonetic encoding, clustering, similarity, CSV parsing and export - runs in your browser; no name is ever uploaded. Input is capped at 2,000 names and the code table renders at most 400 rows, but clustering, dedupe and export still cover every name you pasted.

  • 100% free — no account needed
  • Runs in your browser
  • Nothing is uploaded

Frequently asked questions

Is Phonetic Name Matcher really free?

Yes. Phonetic Name Matcher is completely free on PureBrowser — every feature, with no account, no trial, and no credit card.

Does Phonetic Name Matcher upload my data?

No. Phonetic Name Matcher runs entirely inside your browser, so anything you type, paste, or open stays on your own device.

Do I need to sign up or install anything?

Neither. There is no account and nothing to download — open the page and Phonetic Name Matcher is ready to use on desktop or mobile.

Does Phonetic Name Matcher work offline?

Once the page has loaded, yes. All of the processing happens locally in your browser, so it keeps working without a connection.