This paper deals with the impact of a signal enhancement method on speech recognition confidence scores, in the presence of noise. The speech recognition confidence score reflects the reliability of correctness of the recogniser’s output. This is important since errors in the presence of noise are more frequent and tend to make applications, such as spoken dialogue systems, too cumbersome to use. By recognising enhanced signals not only the word error rate decreases but also the word-based confidence scores decline. Therefore, the role of speech recognition in spoken dialogue systems weakens. The experimentation involves input signal corrupted by coloured noise and cocktail party noise with varying Signal-to-Noise Ratio. A non-linear spectral subtraction method (NSS) will be used in conjunction with the Continuous Speech Recognition system developed for the ERMIS project (IST-2000-29319) to quantify the impact of speech enhancement on confidence score accuracy.