diff --git a/README.md b/README.md
index dc20967..4cab00b 100755
--- a/README.md
+++ b/README.md
@@ -282,7 +282,7 @@ Notice of course since the matching itself is single threaded, the matching time
     
 if we disregard the miniscule constant term.
 
-The overhead of peak finding is the bottleneck - I experimented with mutlithreading and realtime matching, and alas, it wasn't meant to be in Python. An equivalent Java or C/C++ implementation would most likely have little trouble keeping up, applying FFT and peakfinding in realtime.
+The overhead of peak finding is the bottleneck - I experimented with multithreading and realtime matching, and alas, it wasn't meant to be in Python. An equivalent Java or C/C++ implementation would most likely have little trouble keeping up, applying FFT and peakfinding in realtime.
 
 An important caveat is of course, the round trip time (RTT) for making matches. Since my MySQL instance was local, I didn't have to deal with the latency penalty of transfering fingerprint matches over the air. This would add RTT to the constant term in the overall calculation, but would not effect the matching process.