One of the basic aspects of modern pattern matching algorithms used in speech recognition is time-alignment. The use of time-alignment is essential for offsetting speaking rate variations, which is an inherent property of the speech signal. It is known that time-alignment contributes to increased accuracy in speech recognition. However, a key question is whether time-alignment information still contributes to recognition accuracy in highly degraded speech. In this paper we examine the robustness of time-alignment information by introducing a robustness indicator. Isolated words recognition experiments with and without time alignment (using DTW and VQ respectively) are used and to illustrate the issue.