diff --git a/README.rst b/README.rst
index 0d0322b9..4b224960 100644
--- a/README.rst
+++ b/README.rst
@@ -34,6 +34,8 @@ Speech recognition engine/API support:
 * `Houndify API <https://houndify.com/>`__
 * `IBM Speech to Text <http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/speech-to-text.html>`__
 * `Snowboy Hotword Detection <https://snowboy.kitt.ai/>`__ (works offline)
+* `Tensorflow <https://www.tensorflow.org/>`__
+* `Vosk API <https://github.com/alphacep/vosk-api/>`__ (works offline)
 
 **Quickstart:** ``pip install SpeechRecognition``. See the "Installing" section for more details.
 
@@ -52,6 +54,8 @@ The `library reference <https://github.com/Uberi/speech_recognition/blob/master/
 
 See `Notes on using PocketSphinx <https://github.com/Uberi/speech_recognition/blob/master/reference/pocketsphinx.rst>`__ for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under ``reference/pocketsphinx.rst``.
 
+You have to install Vosk models for using Vosk. `Here <https://alphacephei.com/vosk/models>`__ are models avaiable. You have to place them in models folder of your project, like "your-project-folder/models/your-vosk-model"
+
 Examples
 --------
 
@@ -86,6 +90,7 @@ To use all of the functionality of the library, you should have:
 * **PocketSphinx** (required only if you need to use the Sphinx recognizer, ``recognizer_instance.recognize_sphinx``)
 * **Google API Client Library for Python** (required only if you need to use the Google Cloud Speech API, ``recognizer_instance.recognize_google_cloud``)
 * **FLAC encoder** (required only if the system is not x86-based Windows/Linux/OS X)
+* **Vosk** (required only if you need to use Vosk API speech recognition ``recognizer_instance.recognize_vosk``)
 
 The following requirements are optional, but can improve or extend functionality in some situations:
 
@@ -129,6 +134,16 @@ Note that the versions available in most package repositories are outdated and w
 
 See `Notes on using PocketSphinx <https://github.com/Uberi/speech_recognition/blob/master/reference/pocketsphinx.rst>`__ for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under ``reference/pocketsphinx.rst``.
 
+Vosk (for Vosk users)
+~~~~~~~~~~~~~~~~~~~~~
+Vosk API is **required if and only if you want to use Vosk recognizer** (``recognizer_instance.recognize_vosk``).
+
+You can install it with ``python3 -m pip install vosk``.
+
+You also have to install Vosk Models:
+
+`Here <https://alphacephei.com/vosk/models>`__ are models avaiable for download. You have to place them in models folder of your project, like "your-project-folder/models/your-vosk-model"
+
 Google Cloud Speech Library for Python (for Google Cloud Speech API users)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/speech_recognition/__init__.py b/speech_recognition/__init__.py
index 8eaabf94..37b17292 100644
--- a/speech_recognition/__init__.py
+++ b/speech_recognition/__init__.py
@@ -1390,7 +1390,24 @@ def recognize_tensorflow(self, audio_data, tensor_graph='tensorflow-data/conv_ac
             for node_id in top_k:
                 human_string = self.tflabels[node_id]
                 return human_string
-
+            
+    def recognize_vosk(self, audio_data, language='en'):
+        from vosk import Model, KaldiRecognizer
+        
+        assert isinstance(audio_data, AudioData), "Data must be audio data"
+        
+        if not hasattr(self, 'vosk_model'):
+            if not os.path.exists("model"):
+                return "Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder."
+                exit (1)
+            self.vosk_model = Model("model")
+
+        rec = KaldiRecognizer(self.vosk_model, 16000);
+        
+        rec.AcceptWaveform(audio_data.get_raw_data(convert_rate=16000, convert_width=2));
+        finalRecognition = rec.FinalResult()
+        
+        return finalRecognition
 
 def get_flac_converter():
     """Returns the absolute path of a FLAC converter executable, or raises an OSError if none can be found."""