<p>Let's assume that your sentence-similarity scheme uses only word-vectors as an input – as in simple word-vector averaging schemes, or Word Mover's Distance. </p>

<p>It should be possible to do what you've suggested, provided that:</p>

<ul>
<li>you have good sets of word-vectors for each language's words</li>
<li>the coordinate spaces of the word-vectors are compatible, meaning the words for the exact-same things in both languages have nearly-identical coordinates (and other words with similar meanings have close coordinates)</li>
</ul>

<p>That second quality is not automatically assured. In fact, given the random initialization of word2vec models, and other randomization introduced by the algorithm/implementation, even subsequent training runs on the exact same data won't place words into the exact same places. So word-vectors trained on totally-separate English/Dutch corpuses won't likely place equivalent words at the same coordinates. </p>

<p>But, you can learn an algebraic-transformation between two spaces, based on certain anchor/reference word-pairs (that you know should have similar vectors). You can then apply that transformation to all words in one of the two sets, which results in you having vectors for those 'foreign' words within the comparable coordinate-space of the 'canonical' word-set. </p>

<p>In fact this very idea was used in one of the first word2vec papers:</p>

<p>"<a href="https://arxiv.org/abs/1309.4168" rel="nofollow noreferrer">Exploiting Similarities among Languages for Machine Translation</a>"</p>

<p>If you were to apply a similar transformation on one of your language word-vector sets, then use those transformed vectors as inputs to your sentence-vector scheme, those sentence-vectors would likely have some useful comparability to sentence-vectors in the other language, bootstrapped from word-vectors in the same coordinate-space. </p>

<p><strong>Update:</strong> There's a very interesting <a href="https://arxiv.org/abs/1601.02502" rel="nofollow noreferrer">recent paper</a> that manages to train word-vectors in multiple languages simultaneously, using a corpus that includes both raw sentences in each single language, and a (smaller) set of aligned-sentences that are known to mean the same in both languages. Gensim doesn't yet support this mode, but there's <a href="https://groups.google.com/d/msg/gensim/zksGwKHnIUA/7lde13FbAgAJ" rel="nofollow noreferrer">discussion of supporting it</a> in a future refactor.  </p>
Semantic Similarity across multiple languages
<p>I am using word embeddings for finding similarity between two sentences. Using word2vec, I also get a similarity measure if one sentence is in English and the other one in Dutch (though not very good). </p>

<p>So I started wondering if it's possible to compute the similarity between two sentences in two different languages (without an explicit translation), especially if the languages have some similarities (Englis/Dutch)?</p>