The aim of this paper was to analyze the influence of narrow-band input channel on a broadcast news speech recognition system. Different acoustic conditions can be found within a typical broadcast news domain, where narrow-band channel presents one of those with possible high impact on accuracy. A method for acoustic channel detection, based on HMM models is proposed, in order to distinguish between the input channels. The advantage of this method is its low system complexity. The Slovenian BNSI Broadcast News and SNABI speech databases were used for the experimental setup. The Slovenian UMB Broadcast News automatic speech recognizer was applied as a test-bed, modified appropriately for the task. The evaluation of HMM models for channel detection showed accuracy higher than 90% for both channel types. The channel influence analysis confirmed that narrow-band input channel significantly degrades the speech recognition accuracy, decreasing it by more than 13% absolute.