diff --git a/doc/design/speech/README.MD b/doc/design/speech/deep_speech_2.md
similarity index 85%
rename from doc/design/speech/README.MD
rename to doc/design/speech/deep_speech_2.md
index 7304650e628dba210488cd2dc4836318b5383b2a..cfdc4d6df04344c70d3334626bd38eca997c31ff 100644
--- a/doc/design/speech/README.MD
+++ b/doc/design/speech/deep_speech_2.md
@@ -140,7 +140,19 @@ TODO by Assignees
 
 ### Beam Search with CTC and LM
 
-TODO by Assignees
+<div align="center">
+<img src="image/beam_search.png" width=600><br/>
+Figure 2. Algorithm for CTC Beam Search Decoder.
+</div>
+
+- The **Beam Search Decoder** for DS2 CTC-trained network follows the similar approach in \[[3](#references)\] as shown in Figure 2, with two important modifications for the ambiguous parts: 
+   - 1) in the iterative computation of probabilities, the assignment operation is changed to accumulation for one prefix may comes from different paths; 
+   - 2) the if condition ```if l^+ not in A_prev then``` after probabilities' computation is deprecated for it is hard to understand and seems unnecessary.
+- An **external scorer** would be passed into the decoder to evaluate a candidate prefix during decoding whenever a white space appended in English decoding and any character appended in Mandarin decoding.
+- Such external scorer consists of language model, word count or any other custom scorers.
+- The **language model** is built from Task 5, with parameters should be carefully tuned to achieve minimum WER/CER (c.f. Task 7)
+- This decoder needs to perform with **high efficiency** for the convenience of parameters tuning and speech recognition in reality. 
+ 
 
 ## Future Work
 
@@ -153,3 +165,4 @@ TODO by Assignees
 
 1. Dario Amodei, etc., [Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin](http://proceedings.mlr.press/v48/amodei16.pdf). ICML 2016.
 2. Dario Amodei, etc., [Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin](https://arxiv.org/abs/1512.02595). 	arXiv:1512.02595.
+3. Awni Y. Hannun, etc. [First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs](https://arxiv.org/abs/1408.2873). arXiv:1408.2873
diff --git a/doc/design/speech/image/beam_search.png b/doc/design/speech/image/beam_search.png
new file mode 100644
index 0000000000000000000000000000000000000000..7f7e35f34223162d0f7f0ed97375909c43b830ae
Binary files /dev/null and b/doc/design/speech/image/beam_search.png differ