The adequacies of the simulation-based assessment of speech recognition systems under noisy conditions are investigated and discussed. To evaluate the speech recognition systems in various environments, it is desirable to collect the test data uttered in the corresponding environments but it is not realistic since enormous works are required. To conduct evaluations of the speech recognition systems properly, it is promising to simulate evaluation experiments in the target environments as described below: comparatively small test data are collected, and test data of the target environment are generated by computing convolution of the impulse response of the target environment with the collected data. However, it is well known that changes of the acoustic characteristics are caused by Lombard effect, and so it is not necessarily obvious whether the simulation can precisely approximate the experiment in actual environment. This paper clarifies the condition to perform effective simulations of the noisy speech recognition, focusing on the influence of impulse response accuracies and Lombard effects on the speech recognition performance.