  We explore the use of segments learnt using Byte Pair Encoding (referred to
as BPE units) as basic units for statistical machine translation between
related languages and compare it with orthographic syllables, which are
currently the best performing basic units for this translation task. BPE
identifies the most frequent character sequences as basic units, while
orthographic syllables are linguistically motivated pseudo-syllables. We show
that BPE units modestly outperform orthographic syllables as units of
translation, showing up to 11% increase in BLEU score. While orthographic
syllables can be used only for languages whose writing systems use vowel
representations, BPE is writing system independent and we show that BPE
outperforms other units for non-vowel writing systems too. Our results are
supported by extensive experimentation spanning multiple language families and
writing systems.
