--- a/slide.md	Thu Jun 25 06:07:48 2015 +0900
+++ b/slide.md	Fri Jun 26 09:09:58 2015 +0900
@@ -164,7 +164,7 @@
 # Implementation on ARMAR-IIIb
 * ARMAR-III is designed for close cooperation with humans
 * ARMAR-III has a humanlike appearance
-* sensory capabilities similar to humans(
+* sensory capabilities similar to humans
 * ARMAR-IIIb is a slightly modified version with different shape to the head, the trunk, and the hands
 
 # Implementation of gestures
@@ -177,18 +177,21 @@
 * providing a unified representation of various human motion capture systems, action recognition systems, imitation systems, visualization modules
 * This representation can be subsequently converted to other representations, such as action recognizers, 3D visualization, or implementation into different robots
 * The MMM is intended to become a common standard in the robotics community
+
+# Master Motor Map
 <img src="pictures/MMM.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 
-# Master Motor Map2
+# Master Motor Map
 * The body model of MMM  model can be seen in the left-hand illustration in Figure 
 * It contains some joints, such as the clavicula, which are usually not implemented in humanoid robots
 * A conversion module is necessary to perform a transformation between this kinematic model and ARMAR-IIIb kinematic model
+
+# Master Motor Map
 <img src="pictures/MMMModel.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 
 # converter
 * converter given joint angles would consist in a one-to-one mapping between an observed human subject and the robot
-* differences in the kinematic structures of a human and the robot one-to-one mapping can hardly show acceptable results in terms of a human like appearance of the reproduced movement
-* this problem is addressed by applying a post-processing procedure in joint angle space
+* convert is addressed by applying a post-processing procedure in joint angle space
 * the joint angles, given in the MMM format,are optimized concerning the tool centre point position
 * solution is estimated by using the joint configuration of the MMM model on the robot
 
@@ -201,7 +204,6 @@
 
 # Conversion example of MMM
 * After programming the postures directly on the MMM model  they were processed by the converter
-* Conversion is not easy
 * the human model contains many joints, which are not present in the robot configuration
 * ARMAR is not bending the body when performing a bow
 * It was expressed using a portion present in the robot (e.g., the neck)
@@ -217,6 +219,8 @@
 * The postures could be triggered from the MCA (Modular Controller Architecture, a modular software framework)interface, where the greetings model was also implemented
 * the list of postures is on the left together with the option
 * When that option is activated, it is possible to select the context parameters through the radio buttons on the right
+
+#  Modular Controller Architecture, a modular software framework
 <img src="pictures/MCA.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 
 # Implementation of words
@@ -237,8 +241,8 @@
 * added two small speakers behind the head and connected them to another computer
 
 # Experiment description
-* Experiments were conducted at room as shown in Figure 9 , Germany
-<img src="pictures/room.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
+* Experiments were conducted at room as shown in Figure , Germany
+<img src="pictures/room.png" style='width: 60%; margin-left: 150px; margin-top: 50px;'>
 
 
 # Experiment description2
@@ -268,11 +272,6 @@
 2. average age: 29.43
 3. age standard deviation: 12.46
 
-# The purpose of the experiment
-* The objective of the experiment was to adapt ARMAR-IIIb greeting behaviour from Japanese to German culture
-* the algorithm working for ARMAR was trained with only Japanese sociology data and two mappings M0J were built for gestures and words
-* After interacting with German people, the resulting mappings M1 were expected to synthesize the rules of greeting interaction in Germany
-
 # The experiment protocol is as follows 1~5
 1. ARMAR-IIIb is trained with Japanese data
 2. encounter are given as inputs to the algorithm and the robot is prepared
@@ -292,28 +291,28 @@
 * It has become common Bowing is greatly reduced handshake
 * It has appeared hug that does not exist in Japan of mapping 
 * This is because the participants issued a feedback that hug is appropriate
+
+# Results
 <img src="pictures/GestureTable.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 
-# Results2
+# Results
 * The biggest change in the words of the mapping , are gone workplace of greeting
 * Is the use of informal greeting as a small amount of change
-* some other patterns can be found in the gestures mappings judging from the columns in Table 3 for T = 0
-* Japan there is a pattern to the gesture by social distance
-* But in Germany not the pattern
-* This is characteristic of Japanese society
-* The two mapping has been referring to the feedback of the Japanese sociology literature and the German participants
+
+# Results
 <img src="pictures/GreetingWordTable.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 
 # Limitations and improvements
-* In the current implementation, there are also a few limitations
 * The first obvious limitation is related to the manual input of context data
-* →　 The integrated use of cameras would make it possible to determine features such as gender, age, and race of the human
+* The integrated use of cameras would make it possible to determine features such as gender, age, and race of the human
+
+# Limitations and improvements
+* Robot itself , to determine whether the greeting was correct
 * Speech recognition system and cameras could also detect the human own greeting
-* → Robot itself , to determine whether the greeting was correct
 * The decision to check the distance to the partner , the timing of the greeting , head orientation , or to use other information , whether the response to a greeting is correct and what is expected
-* Accurate der than this information is information collected using a questionnaire
+
+#Limitations and improvements
 * It is possible to extend the set of context by using a plurality of documents
-* This in simplification of greeting model was canceled
 
 # Different kinds of embodiment
 * Humanoid robot has a body similar to the human