Update release notes

Author: pemistahl

README.md

@@ -790,7 +790,7 @@ including mean, median and standard deviation.
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@@ -3252,8 +3252,8 @@ including mean, median and standard deviation.
 	</tr>
 	<tr>
 		<td>Ukrainian</td>
-		<td><img src="https://raw.githubusercontent.com/pemistahl/lingua-py/pure-python-impl/images/green.png"> 92</td>
-		<td><img src="https://raw.githubusercontent.com/pemistahl/lingua-py/pure-python-impl/images/green.png"> 86</td>
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RELEASE_NOTES.md

@@ -1,4 +1,4 @@
-## Lingua 1.3.5 (released on 08 Dec 2023)
+## Lingua 1.3.5 (released on 03 Apr 2024)
 
 ### Improvements
 
@@ -8,6 +8,17 @@
   performance was much too slow with the former approach, this change makes
   sense because adding more memory is quite cheap.
 
+- The language model files are now compressed with the Brotli algorithm which
+  reduces the file size by 15 %, on average.
+
+- The characters `Щщ` are now correctly identified as possible indicators for
+  the Ukrainian language, leading to slightly higher accuracy when identifying
+  Ukrainian texts.
+
+### Miscellaneous
+
+- All dependencies have been updated to their latest versions.
+
 ## Lingua 1.3.4 (released on 07 Nov 2023)
 
 ### Miscellaneous

accuracy-reports/aggregated-accuracy-values.csv

@@ -9,7 +9,7 @@ Belarusian,NaN,NaN,NaN,NaN,76,42,87,99,84,67,86,100,85,69,87,99,85,69,88,98,92,8
 Bengali,NaN,NaN,NaN,NaN,63,19,69,99,99,98,99,99,92,92,88,97,98,94,99,100,98,94,99,100,98,94,99,100,100,100,100,100,100,100,100,100,100,100,100,100
 Bokmal,50,15,45,90,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,13,3,12,23,NaN,NaN,NaN,NaN,69,53,70,85,75,55,77,91,NaN,NaN,NaN,NaN,50,27,47,75,58,39,59,77
 Bosnian,NaN,NaN,NaN,NaN,19,4,15,36,33,19,28,52,5,2,4,8,9,9,10,8,54,54,64,44,65,54,76,64,NaN,NaN,NaN,NaN,29,23,29,36,35,29,35,41
-Bulgarian,68,44,67,91,66,32,72,93,70,45,66,98,67,46,62,93,78,56,81,99,89,80,88,98,92,83,95,99,72,50,68,96,78,56,81,96,87,70,91,99
+Bulgarian,68,44,67,91,66,32,72,93,70,45,66,98,67,46,62,93,78,56,81,99,89,80,88,98,92,83,95,99,72,50,68,97,78,56,81,96,87,70,91,99
 Catalan,59,32,62,81,38,4,30,79,48,19,42,84,38,5,29,81,57,33,57,83,63,42,63,85,66,44,67,88,55,26,52,87,58,33,60,82,70,51,74,87
 Chinese,NaN,NaN,NaN,NaN,33,NaN,2,98,92,92,83,100,96,90,97,100,71,46,68,100,71,46,68,100,71,46,68,100,64,39,55,97,100,100,100,100,100,100,100,100
 Croatian,NaN,NaN,NaN,NaN,51,34,47,73,42,26,42,58,48,16,38,90,47,28,42,72,72,62,79,76,81,64,87,93,73,50,71,98,60,36,57,86,73,53,74,90
@@ -67,7 +67,7 @@ Thai,NaN,NaN,NaN,NaN,100,100,100,100,99,100,100,98,100,100,100,100,100,100,100,1
 Tsonga,NaN,NaN,NaN,NaN,61,19,68,97,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,72,46,73,97,84,66,89,98
 Tswana,NaN,NaN,NaN,NaN,56,17,57,94,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,71,44,73,96,84,65,88,99
 Turkish,76,55,78,96,66,30,71,97,69,41,70,97,67,50,67,84,86,70,88,100,86,70,88,100,86,70,88,100,82,62,84,100,87,71,91,99,94,84,98,100
-Ukrainian,78,62,75,97,77,46,88,99,81,62,83,98,76,54,77,96,91,78,94,100,95,90,95,100,98,94,98,100,83,66,85,97,86,75,92,93,92,84,97,95
+Ukrainian,78,62,75,97,77,46,88,99,81,62,83,98,76,54,77,96,91,78,94,100,95,90,95,100,98,94,98,100,83,66,85,98,88,75,92,96,94,85,98,99
 Urdu,NaN,NaN,NaN,NaN,61,8,75,99,61,39,53,92,58,30,46,99,63,40,50,99,75,59,68,99,80,68,74,99,83,67,84,97,79,65,78,94,90,80,94,96
 Vietnamese,NaN,NaN,NaN,NaN,63,NaN,90,100,66,26,74,99,86,65,93,100,89,71,97,100,89,71,97,100,89,71,97,100,93,81,97,100,87,75,87,98,91,79,94,99
 Welsh,69,58,60,90,72,34,85,98,69,43,66,98,49,11,39,95,64,35,61,96,69,41,71,96,72,46,74,97,85,69,88,99,82,61,87,99,91,78,96,99

accuracy-reports/lingua-high-accuracy/Bulgarian.txt

@@ -1,10 +1,10 @@
 ##### Bulgarian #####
 
->>> Accuracy on average: 86.80%
+>>> Accuracy on average: 86.70%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 70.20%
-Erroneously classified as Macedonian: 12.80%, Russian: 9.40%, Serbian: 4.10%, Ukrainian: 1.60%, Kazakh: 0.80%, Belarusian: 0.60%, Mongolian: 0.50%
+Accuracy: 69.90%
+Erroneously classified as Macedonian: 12.80%, Russian: 9.40%, Serbian: 4.10%, Ukrainian: 1.90%, Kazakh: 0.80%, Belarusian: 0.60%, Mongolian: 0.50%
 
 >> Detection of 1000 word pairs (average length: 17 chars)
 Accuracy: 91.20%

accuracy-reports/lingua-high-accuracy/Russian.txt

@@ -1,10 +1,10 @@
 ##### Russian #####
 
->>> Accuracy on average: 89.70%
+>>> Accuracy on average: 89.67%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 76.50%
-Erroneously classified as Ukrainian: 6.30%, Bulgarian: 5.50%, Serbian: 3.40%, Belarusian: 3.30%, Macedonian: 3.00%, Mongolian: 1.10%, Kazakh: 0.90%
+Accuracy: 76.40%
+Erroneously classified as Ukrainian: 6.40%, Bulgarian: 5.50%, Serbian: 3.40%, Belarusian: 3.30%, Macedonian: 3.00%, Mongolian: 1.10%, Kazakh: 0.90%
 
 >> Detection of 1000 word pairs (average length: 16 chars)
 Accuracy: 94.80%

accuracy-reports/lingua-high-accuracy/Ukrainian.txt

@@ -1,16 +1,16 @@
 ##### Ukrainian #####
 
->>> Accuracy on average: 92.23%
+>>> Accuracy on average: 93.77%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 84.40%
-Erroneously classified as Russian: 4.90%, Serbian: 3.40%, Bulgarian: 2.60%, Belarusian: 2.20%, Macedonian: 1.40%, Mongolian: 0.90%, Kazakh: 0.20%
+Accuracy: 85.00%
+Erroneously classified as Russian: 4.50%, Serbian: 3.40%, Bulgarian: 2.40%, Belarusian: 2.20%, Macedonian: 1.40%, Mongolian: 0.90%, Kazakh: 0.20%
 
 >> Detection of 1000 word pairs (average length: 17 chars)
-Accuracy: 97.30%
-Erroneously classified as Russian: 1.00%, Bulgarian: 0.50%, Serbian: 0.50%, Macedonian: 0.40%, Belarusian: 0.30%
+Accuracy: 97.50%
+Erroneously classified as Russian: 0.80%, Bulgarian: 0.50%, Serbian: 0.50%, Macedonian: 0.40%, Belarusian: 0.30%
 
 >> Detection of 1000 sentences (average length: 108 chars)
-Accuracy: 95.00%
-Erroneously classified as Kazakh: 4.10%, Belarusian: 0.30%, Macedonian: 0.30%, Russian: 0.30%
+Accuracy: 98.80%
+Erroneously classified as Belarusian: 0.30%, Kazakh: 0.30%, Macedonian: 0.30%, Russian: 0.30%
 

accuracy-reports/lingua-low-accuracy/Bulgarian.txt

@@ -1,10 +1,10 @@
 ##### Bulgarian #####
 
->>> Accuracy on average: 77.83%
+>>> Accuracy on average: 77.77%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 56.40%
-Erroneously classified as Macedonian: 13.20%, Russian: 12.50%, Serbian: 6.20%, Kazakh: 3.60%, Ukrainian: 3.50%, Belarusian: 2.40%, Mongolian: 2.20%
+Accuracy: 56.20%
+Erroneously classified as Macedonian: 13.20%, Russian: 12.50%, Serbian: 6.20%, Ukrainian: 3.80%, Kazakh: 3.60%, Belarusian: 2.40%, Mongolian: 2.10%
 
 >> Detection of 1000 word pairs (average length: 17 chars)
 Accuracy: 80.60%

accuracy-reports/lingua-low-accuracy/Russian.txt

@@ -1,14 +1,14 @@
 ##### Russian #####
 
->>> Accuracy on average: 78.47%
+>>> Accuracy on average: 78.37%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 59.20%
-Erroneously classified as Ukrainian: 8.40%, Macedonian: 8.20%, Bulgarian: 6.60%, Serbian: 5.30%, Belarusian: 4.80%, Mongolian: 4.00%, Kazakh: 3.50%
+Accuracy: 59.10%
+Erroneously classified as Ukrainian: 8.60%, Macedonian: 8.20%, Bulgarian: 6.60%, Serbian: 5.30%, Belarusian: 4.80%, Mongolian: 4.00%, Kazakh: 3.40%
 
 >> Detection of 1000 word pairs (average length: 16 chars)
-Accuracy: 83.90%
-Erroneously classified as Macedonian: 4.80%, Ukrainian: 4.30%, Bulgarian: 2.60%, Serbian: 1.80%, Mongolian: 1.10%, Belarusian: 1.00%, Kazakh: 0.50%
+Accuracy: 83.70%
+Erroneously classified as Macedonian: 4.80%, Ukrainian: 4.50%, Bulgarian: 2.60%, Serbian: 1.80%, Mongolian: 1.10%, Belarusian: 1.00%, Kazakh: 0.50%
 
 >> Detection of 1000 sentences (average length: 65 chars)
 Accuracy: 92.30%

accuracy-reports/lingua-low-accuracy/Ukrainian.txt

@@ -1,16 +1,16 @@
 ##### Ukrainian #####
 
->>> Accuracy on average: 86.33%
+>>> Accuracy on average: 87.87%
 
 >> Detection of 1000 single words (average length: 8 chars)
-Accuracy: 74.70%
-Erroneously classified as Russian: 6.50%, Serbian: 5.40%, Belarusian: 3.90%, Macedonian: 3.80%, Bulgarian: 2.10%, Kazakh: 1.90%, Mongolian: 1.70%
+Accuracy: 75.30%
+Erroneously classified as Russian: 6.20%, Serbian: 5.40%, Belarusian: 3.90%, Macedonian: 3.80%, Kazakh: 1.90%, Bulgarian: 1.80%, Mongolian: 1.70%
 
 >> Detection of 1000 word pairs (average length: 17 chars)
-Accuracy: 91.60%
-Erroneously classified as Russian: 3.20%, Serbian: 1.90%, Belarusian: 1.00%, Bulgarian: 0.70%, Macedonian: 0.70%, Mongolian: 0.70%, Kazakh: 0.20%
+Accuracy: 91.80%
+Erroneously classified as Russian: 3.00%, Serbian: 1.90%, Belarusian: 1.00%, Bulgarian: 0.70%, Macedonian: 0.70%, Mongolian: 0.70%, Kazakh: 0.20%
 
 >> Detection of 1000 sentences (average length: 108 chars)
-Accuracy: 92.70%
-Erroneously classified as Kazakh: 4.10%, Macedonian: 2.10%, Russian: 0.40%, Belarusian: 0.30%, Bulgarian: 0.20%, Serbian: 0.20%
+Accuracy: 96.50%
+Erroneously classified as Macedonian: 2.10%, Russian: 0.40%, Belarusian: 0.30%, Kazakh: 0.30%, Bulgarian: 0.20%, Serbian: 0.20%
 

images/plots/barplot-average.png

@@ -80,7 +80,16 @@
     "ЁёЫыЭэ": frozenset(
         [Language.BELARUSIAN, Language.KAZAKH, Language.MONGOLIAN, Language.RUSSIAN]
     ),
-    "ЩщЪъ": frozenset(
+    "Щщ": frozenset(
+        [
+            Language.BULGARIAN,
+            Language.KAZAKH,
+            Language.MONGOLIAN,
+            Language.RUSSIAN,
+            Language.UKRAINIAN,
+        ]
+    ),
+    "Ъъ": frozenset(
         [Language.BULGARIAN, Language.KAZAKH, Language.MONGOLIAN, Language.RUSSIAN]
     ),
     "Òò": frozenset(

images/plots/barplot-sentences.png

@@ -463,7 +463,13 @@ def test_language_detection_with_rules(word, expected_language):
         ),
         pytest.param(
             "плаваща",
-            [Language.BULGARIAN, Language.KAZAKH, Language.MONGOLIAN, Language.RUSSIAN],
+            [
+                Language.BULGARIAN,
+                Language.KAZAKH,
+                Language.MONGOLIAN,
+                Language.RUSSIAN,
+                Language.UKRAINIAN,
+            ],
         ),
         pytest.param(
             "довършат",