Several techniques have been used to constraint the search space in an HMM based continuous speech recognition system (grammar, beam search, etc.) in order to reduce computation without significant lose in performance [1]. The use of anchor points is a state-of-the-art technique that has already been used in some systems [2][3][4]. This approach has lead us to a bottom-up strategy in a continuous speech recognition system in which the first module performs the spotting of predefined phonetic events and the second module uses them as anchor points in order to guide the HMM-based recognition task. This paper describes the definition of phonetic events for Spanish (based on expert knowledge of language) and the algorithms used for their detection and classification. Figures of performance are presented.