Stress and syllabification are essential attributes for several components in text-to speech (TTS) systems. They are responsible for improving grapheme-to-phoneme conversion rules and for enhancing the synthetic intelligibility, since stress and syllable are key units in prosody prediction. This paper presents three linguistically rule-based automatic algorithms for Catalan text-to-speech conversion: a word stress marker, an orthographic syllabification algorithm and a phonological syllabification algorithm. The systems were implemented and tested. The results gave rise to the following word accuracy rates: 100% for the stress marker algorithm, 99.7% for the orthographic syllabification algorithm and 99.8% for the phonological syllabification algorithm.