diff --git a/.appveyor.yml b/.appveyor.yml
index 8f0a21967..4dcd75e9c 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -8,16 +8,24 @@ environment:
   matrix:
 
     # Python 2.7.10 is the latest version and is not pre-installed.
-
     - PYTHON: "C:\\Python27.10-x64"
       PYTHON_VERSION: "2.7.10"
       PYTHON_ARCH: "64"
 
+    - PYTHON: "C:\\Python27.10-x32"
+      PYTHON_VERSION: "2.7.10"
+      PYTHON_ARCH: "32"
+
     # The lastest Python 3.4.
     - PYTHON: "C:\\Python34-x64" 
       PYTHON_VERSION: "3.4.x" # currently 3.4.3 
       PYTHON_ARCH: "64" 
 
+    #- PYTHON: "C:\\Python34-x32" 
+    #  PYTHON_VERSION: "3.4.x" # currently 3.4.3 
+    #  PYTHON_ARCH: "32" 
+
+
 install:
   # Install Python (from the official .msi of http://python.org) and pip when
   # not already installed.
@@ -30,10 +38,11 @@ install:
   - "SET PYTHONPATH=%CD%;%PYTHONPATH%"
 
   # Filesystem root
-  # - ps: "ls \"C:/\""
+  #- ps: "ls \"C:/\""
+  #- SET
 
   # Installed SDKs
-  # - ps: "ls \"C:/Program Files/Microsoft SDKs/Windows\""
+  #- ps: "ls \"C:/Program Files/Microsoft SDKs/Windows\""
 
   # Checking stdint.h
   #- ps: "ls \"C:/projects/spacy/include/\""
diff --git a/README.md b/README.md
index ad384fd2b..8eb39ba01 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,6 @@
+
+<img src="https://ci.appveyor.com/api/projects/status/aoe3dtkep36rdaqf?svg=true" />
+
 spaCy: Industrial-strength NLP
 ==============================
 
@@ -49,3 +52,6 @@ Difficult to support:
 
 * PyPy 2.7
 * PyPy 3.4
+
+
+
diff --git a/spacy/lemmatizer.py b/spacy/lemmatizer.py
index c1d296d7c..08e511f68 100644
--- a/spacy/lemmatizer.py
+++ b/spacy/lemmatizer.py
@@ -19,7 +19,7 @@ class Lemmatizer(object):
             index[pos] = read_index(path.join(data_dir, 'wordnet', 'index.%s' % pos))
             exc[pos] = read_exc(path.join(data_dir, 'wordnet', '%s.exc' % pos))
         if path.exists(path.join(data_dir, 'vocab', 'lemma_rules.json')):
-            rules = json.load(open(path.join(data_dir, 'vocab', 'lemma_rules.json')))
+            rules = json.load(codecs.open(path.join(data_dir, 'vocab', 'lemma_rules.json'), encoding='utf_8'))
         else:
             rules = {}
         return cls(index, exc, rules)