The aim of this paper is to develop an algorithm to enhance speech recognition of a stuttered speech. Stuttering is a disorder that affects the fluency of speech by involuntary repetition, prolongation of words/syllables, or involuntary silent intervals. Current speech recognition systems fail to recognize stuttered speech. Methods to detect stutter have been reported in literature but efficient techniques for stutter correction have not been reported. This paper addresses this issue and proposes methods to detect and correct stutter within acceptable time limits. To remove prolongation(s) from the sample, amplitude thresholding through neural networks is developed. Repetitions are removed through string repetition removal algorithm using an existing Text-to-Speech (TTS) system. Thus, the output signal, void of all stutters, produces better speech recognition.