A phonetic typewriter is an unlimitedvocabulary continuous speech recognition system recognizing each phone in speech without the need for lexical information. This paper describes a Japanese phonetic typewriter system based on HMM phone recognition and syllable-based stochastic phone sequence modeling. Even though HMM methods have considerable capacity for recognizing speech, it is difficult to recognize individual phones in continuous speech without lexical information. HMM phone recognition is improved by incorporating syllable trigrams for phone sequence modeling. HMM phone units are trained using an isolated word database, and their duration parameters are modified according to speaking rate. Syllable trigram tables are made from a text database of over 300,000 syllables, and phone sequence probabilities calculated from the trigrams are combined with HMM probabilities. Using these probabilities, to limit the number of intermediate candidates leads to an accurate phonetic typewriter system without requiring excessive computation time. An interpolated n-gram approach to phone sequence modeling, is shown to be more effective than a simple trigram method.