Annotation of large multilingual corpora remains a challenge to the data-driven approach to speech research, especially for under-resourced languages. This paper presents crosslanguage automatic phonetic segmentation using Hidden Markov Models (HMMs). The underlying notion is segmentation based on articulation (manner and place) so as to provide extensive models that will be applicable across languages. A test on the Appen Spanish speech corpus gives