Natural language communication is very important in Human-Robot cooperative systems. As a part of natural language communication, learning to identify natural language references such as "small red cube" is very useful. This paper proposes a method of learning object identification in which the meanings of references such as above can be inferred. The proposed method is demonstrated with an experiment conducted with a PA-10 redundant manipulator and a set of objects. The robot manipulator is issued commands like "pick the big red cube" to identify and pick objects placed on a table. The robot learns to interpret the meaning of this type of natural commands by learning individual lexical symbols in the vocabulary and their corresponding object features.