Since ultimately, the classes used for OCR are Unicode points, the question arises which code points to synthesize additional training data from. We employ the simple heuristic of using all of the glyphs featured in the ground truth, and adding any missing ones from the 4000 most frequent characters of a representative corpus. Furthermore, inconsistencies caused by Han-unification have to be solved. For example, the image data features <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">靑</hi> instead of <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">青</hi> and <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">淸</hi> instead of <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">清</hi> (all different code points), however only one code point exists for every other character containing <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">靑</hi>/ <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">青</hi> as a component ( <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">請</hi>, <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">情</hi>, <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">靜</hi>, …). While <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">值</hi> and <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">値</hi> (the latter being the variant used in our image data) have different code points, their right component itself ( <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">直</hi>) is Han-unified, etc. We decide to always use the most accurate code point as long as it’s not part of the CJK Compatibility Ideographs block (U+F900...U+FAFF), so e.g. <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">令</hi> (U+4EE4) is used instead of <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">令</hi> (U+F9A8), even though the latter might appear more accurate, depending on the font. Generally, we find that the character variants printed in our image data to be visually closer to the Japanese standard (e.g. the components <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">爫</hi> and <hi xmlns="http://www.tei-c.org/ns/1.0" rend="chinese">⺬</hi>), so we choose several Japanese fonts for training data generation.