diff --git a/src/gensim/corpora/bleiextcorpus.py b/src/gensim/corpora/bleiextcorpus.py
new file mode 100644
index 0000000000..e3ab038bd0
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+++ b/src/gensim/corpora/bleiextcorpus.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Extended version of BleiCorpus, has a list-based index
+of all documents for fast retrieval of specific document and length calculation
+"""
+
+import logging, pickle
+
+from gensim.corpora import BleiCorpus
+from gensim import utils
+
+
+class BleiExtCorpus(BleiCorpus):
+    """
+    Corpus in Blei's LDA-C format, extended with index
+    """
+    def __init__(self, fname, fnameVocab = None):
+       super(BleiExtCorpus, self).__init__(fname, fnameVocab)
+       self.index = pickle.load(open(self.fname + '.index', 'r'))
+
+    def __len__(self):
+        return len (self.index)
+
+    def __getitem__(self, id):
+        f = open (self.fname, 'r')
+        f.seek(self.index[id])
+        line = f.readline()
+        parts = line.split()
+        if int(parts[0]) != len(parts) - 1:
+            raise ValueError("invalid format at line %i in %s" % (lineNo, self.fname))
+        doc = [part.rsplit(':', 1) for part in parts[1:]]
+        doc = [(int(p1), float(p2)) for p1, p2 in doc]
+        return doc
+
+    @staticmethod
+    def saveCorpus(fname, corpus, id2word = None):
+        """
+        Save a corpus in the Matrix Market format.
+
+        There are actually three files saved:
+        * `fname`: the corpus itself.
+        * `fname.vocab`: vocabulary file.
+        * `fname.index`: index with pointers to documents.
+        """
+        if id2word is None:
+            logging.info("no word id mapping provided; initializing from corpus")
+            id2word = utils.dictFromCorpus(corpus)
+            numTerms = len(id2word)
+        else:
+            numTerms = 1 + max([-1] + id2word.keys())
+
+        index = []
+        offset = 0
+
+        logging.info("storing corpus in Blei's LDA-C format: %s" % fname)
+        fout = open(fname, 'w')
+        for doc in corpus:
+            doc = list(doc)
+            line = "%i %s\n" % (len(doc), ' '.join("%i:%s" % p for p in doc))
+            fout.write(line)
+            index.append(offset)
+            offset += len(line)
+        fout.close()
+
+        # write out vocabulary, in a format compatible with Blei's topics.py script
+        fnameVocab = fname + '.vocab'
+        logging.info("saving vocabulary of %i words to %s" % (numTerms, fnameVocab))
+        fout = open(fnameVocab, 'w')
+        for featureId in xrange(numTerms):
+            fout.write("%s\n" % utils.toUtf8(id2word.get(featureId, '---')))
+        fout.close()
+
+        # write out index
+        pickle.dump(index, open(fname + '.index', 'w'))