docs: def compute_similarity_scores(self):
          """ Produce a list of similarity scores for each contiguous pair in a response.
  
          Calls compute_similarity_score method for every adjacent pair of words. The results
          are not used in clustering; this is merely to provide a visual representation to
          print to the screen.
  
          Modifies:
              - self.similarity_scores: Fills the list with similarity scores between adjacent
                  words. At this point this list is never used outside of this method.
          """
  
          for i,unit in enumerate(self.parsed_response):
              if i < len(self.parsed_response) - 1:
                  next_unit = self.parsed_response[i + 1]
                  self.similarity_scores.append(self.compute_similarity_score(unit, next_unit))
  
          if not self.quiet:
              print self.current_similarity_measure, "similarity scores (adjacent) -- higher is closer:"
              table = [("Word 1", "Word 2", "Score")] + \
                      [(self.parsed_response[i].text, self.parsed_response[i + 1].text,
                        "{0:.3f}".format(round(self.similarity_scores[i], 2)))
                       for i in range(len(self.parsed_response)-1)]
              print_table(table)