diff --git a/README.md b/README.md
index 245d204..d1a855c 100755
--- a/README.md
+++ b/README.md
@@ -49,7 +49,7 @@ Get *discrete cosine transform* (DCT) coefficients and quantization matrices as
 
 
 ```python
-im = jpeglib.read_dct("input.jpeg")
+im = jpeglib.read_dct('input.jpeg')
 im.Y; im.Cb; im.Cr; im.qt
 ```
 
@@ -58,7 +58,7 @@ You get luminance DCT, chrominance DCT and quantization tables.
 Write the DCT coefficients back to a file with
 
 ```python
-im.write_dct("output.jpeg")
+im.write_dct('output.jpeg')
 ```
 
 ### Pixel data
@@ -66,7 +66,7 @@ im.write_dct("output.jpeg")
 Decompress the `input.jpeg` into spatial representation in numpy array with
 
 ```python
-im = jpeglib.read_spatial("input.jpeg")
+im = jpeglib.read_spatial('input.jpeg')
 im.spatial
 ```
 
@@ -75,7 +75,7 @@ You can specify parameters such as output color space, DCT method, dithering, et
 Write spatial representation in numpy arrray back to file with
 
 ```python
-im.write_spatial("output.jpeg")
+im.write_spatial('output.jpeg')
 ```
 
 You can specify input color space, DCT method, sampling factor, output quality, smoothing factor etc.
@@ -112,5 +112,5 @@ im = jpeglib.read_spatial('image.jpeg') # using 6b again
 
 ## Credits
 
-Developed by [Martin Benes](https://github.com/martinbenes1996), Universität Innsbruck, 2023.
+Developed by [Martin Benes](https://github.com/martinbenes1996), University of Innsbruck, 2023.
 
diff --git a/docs/source/conf.py b/docs/source/conf.py
index cf73128..238abf8 100755
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -5,7 +5,7 @@
 import sphinx_rtd_theme
 
 project = 'jpeglib'
-copyright = '2021, Martin Benes'
+copyright = '2023, Martin Benes'
 author = 'Martin Benes'
 
 release = '0.14'