<p>In the last year a few research groups have started using the character sequence of a word to generate word embedding vectors. See this paper "<a href="http://www.cs.cmu.edu/~lingwang/papers/emnlp2015.pdf" rel="nofollow">Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation</a>" for an example. There is also an earlier paper "<a href="http://arxiv.org/pdf/1405.4273v1.pdf" rel="nofollow">Compositional Morphology for Word Representations and Language Modelling</a>" that specifically uses models morphological differences like differences between singular and plural word forms.</p>

<p>I'm not aware of any open source implementations of these types of models.</p>
word2vec implementation addresing male/female and singular/plural issues
<p>I wonder if you know any word2vec implementation that takes into account that car and cars represents nearly the same concept, or lehrer and lehrerin (German for male and female teacher respectively) are almost the same. The implementations I have seen largely ignore this fact, and therefore the quality of the results is poor.</p>

<p>Thank you in advance.</p>