We have implemented a novel combination of LVQ-codebooks and hidden Markov models (HMMs) for transcribing spoken Finnish words into phonemes. A separate LVQ-codebook was trained for the unvoiced plosives /k/, /p/ and ft/. HMMs were then modified to accommodate two parallel phoneme codebooks and a third codebook representing the power of the speech signal. The error rate of phonemic transcription was as low as 9.1 %. A preliminary test with an additional /b/, /d/ and /g/ codebook was also carried out.