title: NLP - When to lowercase text during preprocessing
body: <p>I want to build a model for language modelling, which should predict the next words in a sentence, given the previous word(s) and/or the previous sentence.</p>
  
  <p><strong>Use case:</strong> I want to automate writing reports. So the model should automatically complete the sentence I am writing. Therefore, it is important that nouns and the words at the beginning of a sentence are capitalized. </p>
  
  <p><strong>Data</strong>: The data is in German and contains a lot of technical jargon.</p>
  
  <p>My text corpus is in <strong>German</strong> and I am currently working on the preprocessing. Because my model should predict gramatically correct sentences I have decided to use/not use the following preprocessing steps:</p>
  
  <ul>
  <li>no stopword removal</li>
  <li><p>no lemmatization</p></li>
  <li><p>replace all expressions with numbers by NUMBER</p></li>
  <li>normalisation of synonyms and abbreviations </li>
  <li>replace rare words with RARE</li>
  </ul>
  
  <p>However, I am not sure whether to convert the corpus to lowercase. When searching the web I found different opinions. Although lower-casing is quite common it will cause my model to wrongly predict the capitalization of nouns, sentence beginnings etc.</p>
  
  <p>I also found the idea to convert only the words at the beginning of a sentence to lower-case on the following <a href="https://nlp.stanford.edu/IR-book/html/htmledition/capitalizationcase-folding-1.html" rel="nofollow noreferrer">Stanford page</a>.</p>
  
  <p>What is the best strategy for this use-case? Should I convert the text to lower-case and change the words to the correct case after prediction? Should I leave the capitalization as it is? Should I only lowercase words at the beginning of a sentence?</p>
  
  <p>Thanks a lot for any suggestions and experiences!</p>