Correctly assessing the degree of mispronunciation and deciding upon the necessary treatment are fundamental activities for all speech disorder specialists. Obviously, the experience and the availability of the specialists are essentials in order to assure an efficient therapy for the speech impaired. To overcome this deficiency a more objective approach would include the existence of a tool that independent of the specialist's abilities could be used to establish the diagnostics. A complete automated system based on speech processing algorithms capable of performing the recognition task is therefore thoroughly justified and can be viewed as a goal that will bring many benefits to the field of speech pronunciation correction. This paper presents further results of the authors' work on developing speech processing algorithms able to identify mispronunciations in Romanian language, more exactly we propose the use of the Walsh-Hadamard Transform (WHT) as feature selection tool in the case of identifying rhotacism. The results are encouraging with a best recognition rate of 92.55%.