diff --git a/do_inject.sh b/inject.sh
similarity index 100%
rename from do_inject.sh
rename to inject.sh
diff --git a/scripts/do_inject.sh b/scripts/do_inject.sh
new file mode 100755
index 0000000..4e18549
--- /dev/null
+++ b/scripts/do_inject.sh
@@ -0,0 +1,19 @@
+#!/bin/bash
+
+# arguments:
+# 1. path to glossary file, E.g. for glossary in ~/data/glossary.tsv should be data/glossary.tsv
+# 2. path to in.tsv file
+# 3. path to expected.tsv file
+# all path should be given as absolute path without ~/ at the very beginning (as seen in the example above)
+
+glossary_path="$1"
+in_path="$2"
+expected_path="$3"
+
+source ~/gpu/bin/activate
+
+cd ~/transfix-mt/scripts
+
+python lemmatize_glossary.py "$glossary_path"
+python lemmatize_in.py "$in_path" "$expected_path"
+python inject.py "$glossary_path" "$in_path" "$expected_path"
diff --git a/scripts/do_inject_helper.sh b/scripts/do_inject_helper.sh
deleted file mode 100755
index f2d62d3..0000000
--- a/scripts/do_inject_helper.sh
+++ /dev/null
@@ -1,9 +0,0 @@
-#!/bin/bash
-
-source ~/gpu/bin/activate
-
-cd ~/transfix-mt/scripts
-
-python lemmatize_glossary.py
-python lemmatize_in.py
-python inject.py
diff --git a/scripts/inject.py b/scripts/inject.py
index dfe8c4e..a9b2bb0 100644
--- a/scripts/inject.py
+++ b/scripts/inject.py
@@ -1,11 +1,21 @@
 import os
 import pandas as pd
 import rapidfuzz
+import sys
 
 from rapidfuzz.fuzz import partial_ratio
 from rapidfuzz.utils import default_process
 
 
+def read_arguments():
+    try:
+        path_glossary, path_in, path_expected = sys.argv
+        return path_glossary, path_in, path_expected
+    except Exception:
+        print("ERROR: Wrong argument.")
+        sys.exit(1)
+
+
 def full_strip(line):
     return ' '.join(line.split())
 
@@ -41,10 +51,11 @@ def get_injected(sentence, sentence_en, sequence, inject):
 
 THRESHOLD = 70
 
-train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/in.tsv')
-train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/expected.tsv')
+glossary_arg_path, in_arg_path, expected_arg_path = read_arguments()
+train_in_path = os.path.join(os.path.expanduser('~'), in_arg_path)
+train_expected_path = os.path.join(os.path.expanduser('~'), expected_arg_path)
 
-glossary = pd.read_csv('~/mt-summit-corpora/glossary.tsv.lemmatized', sep='\t')
+glossary = pd.read_csv(os.path.join(os.path.expanduser('~'), glossary_arg_path), sep='\t')
 glossary['source_lem'] = [str(default_process(x)) for x in glossary['source_lem']]
 glossary['hash'] = [hash(x) for x in glossary['source']]
 glossary = glossary[glossary['hash'] % 100 > 16]
@@ -83,17 +94,17 @@ for line, line_en, line_pl in zip(file_en_lemmatized, file_en, file_pl):
         translation_line_counts.append(1)
         en.append(line_en)
 
-    if len(translation_line_counts) % 50000 == 0:
-        print('injecting into file: ' + train_in_path + '.injected: ' + str(len(translation_line_counts)), end='\r')
+    if len(translation_line_counts) % 1000 == 0:
+        print('injecting into file: ' + train_in_path + ': ' + str(len(translation_line_counts)), end='\r')
 
 print('\n')
 
-with open(train_expected_path + '.injected', 'w') as file_pl_write:
+with open(train_expected_path, 'w') as file_pl_write:
     for line, translation_line_ct in zip(file_pl, translation_line_counts):
         for i in range(translation_line_ct):
             file_pl_write.write(full_strip(line) + '\n')
 
 
-with open(train_in_path + '.injected', 'w') as file_en_write:
+with open(train_in_path, 'w') as file_en_write:
     for e in en:
         file_en_write.write(e + '\n')
diff --git a/scripts/lemmatize_glossary.py b/scripts/lemmatize_glossary.py
index 4096a3b..6bea041 100644
--- a/scripts/lemmatize_glossary.py
+++ b/scripts/lemmatize_glossary.py
@@ -1,14 +1,25 @@
 import nltk
 import os
 import pandas as pd
+import sys
 
 from nltk.stem import WordNetLemmatizer
 
 nltk.download('wordnet')
 
+
+def read_arguments():
+    try:
+        glossary_arg_pathx = sys.argv
+        return glossary_arg_pathx
+    except Exception:
+        print("ERROR: Wrong argument.")
+        sys.exit(1)
+
+
 wl = WordNetLemmatizer()
 
-glossary_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/glossary.tsv')
+glossary_path = os.path.join(os.path.expanduser('~'), read_arguments()[0])
 
 glossary = pd.read_csv(glossary_path, sep='\t', header=None, names=['source', 'result'])
 source_lemmatized = []
diff --git a/scripts/lemmatize_in.py b/scripts/lemmatize_in.py
index 7f9064e..2729870 100644
--- a/scripts/lemmatize_in.py
+++ b/scripts/lemmatize_in.py
@@ -1,13 +1,24 @@
 import nltk
 import os
+import sys
 
 from nltk.stem import WordNetLemmatizer
 
 
+def read_arguments():
+    try:
+        path_in, path_expected = sys.argv
+        return path_in, path_expected
+    except Exception:
+        print("ERROR: Wrong argument.")
+        sys.exit(1)
+
+
 wl = WordNetLemmatizer()
 
-train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/in.tsv')
-train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/expected.tsv')
+in_arg_path, expected_arg_path = read_arguments()
+train_in_path = os.path.join(os.path.expanduser('~'), in_arg_path)
+train_expected_path = os.path.join(os.path.expanduser('~'), expected_arg_path)
 
 file_lemmatized = []
 with open(train_in_path, 'r') as file: