first push

README.md

@@ -1,2 +1,37 @@
-# XlingualEmb
-Crosslingual word embeddings described in our EMNLP paper
+# Speech Translation/Alignment
+This is the implementation of our EMNLP 2016 paper titled : 
+[Learning CrosslingualWord Embeddings without Bilingual Corpora] (https://arxiv.org/abs/1606.09403)
+
+If you use  this code, please cite the paper 
+
+```
+@InProceedings{duong-EtAl:2016:EMNLP,
+  author    = {Duong, Long  and  Kanayama, Hiroshi  and  Ma, Tengfei  and  Bird, Steven  and  Cohn, Trevor},
+  title     = {Learning Crosslingual Word Embeddings without Bilingual Corpora},
+  booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016)},
+  month     = {November},
+  year      = {2016},
+  address   = {Texas, USA},
+  publisher = {Association for Computational Linguistics},
+}
+```
+#### Getting started
+The implementation is basically the extension of C version Word2Vec. You just need to do the make 
+    make
+
+### How to run  
+We included the extracted dictionaries from Panlex for several languages including (German, Dutch, Spanish, Italian, Greek, Finish, Japanse, Serbian) in folder 
+    /data/dicts 
+We also included a tiny mixed English-Italian monolingual data for demo purposes. 
+   /data/mono/en_it.shuf.10k
+The following will build the crosslingual word embeddings for English and Italian. 
+```
+./xlingemb -train data/mono/en_it.shuf.10k -output en.it.word.emb -size 200 -window 48 -iter 15 -negative 25 -sample 0.0001 -alpha 0.025 -cbow 1 -threads 5 -dict data/dicts/en.it.panlex.all.processed -outputn en.it.context.emb -reg 0.01
+```
+Some options :
+- output: the usual word embeddings 
+- outputn : the context word embeddings which is the final output.
+- size, window, iter, negative, sample, alpha, cbow, threads : the same as Word2Vec
+- dict: the dictionary 
+- reg: the regulariser sensitivity for combining word and context embeddings. 
+