Search is perhaps the single most important part of a speech recognizer today. However, we must add many enhancements to these algorithms beyond classic DP to even approach a system capable of performing the tasks embodied in commercial products such as Dragon Systems' Naturally Speaking or IBM's ViaVoice. A reasonable analogy might be DP is to search what wheels are to an automobile. There is a lot more to an automobile beyond its spinning wheels. Search is an essential part of every day life.
Humans perform the complex operations required for efficient searching effortlessly.
We find optimal, or near optimal solutions, with minimal amounts of conscious effort. For example, while writing this editorial, I had the occasion to be traveling through an airport I use frequently during a busy period. I was reminded how experienced travelers soon learn all the tricks required to find the shortest path through an airport. In the early days of speech recognition, we used essentially a one-level DP algorithm. This was easy to implement - the core engine amounted to about 5 lines of code.