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Machine generated speech can be produced in different ways however there are two basic methods for synthesizing speech in widespread use. One method generates speech from models, while the other method concatenates pre-stored speech segments. This paper presents a speech synthesis technique where these two basic synthesis methods are combined in a statistical framework. Synthetic speech is constructed by generation and concatenation of so-called "multiform segments". Multiform segments are different speech signal representations; synthesis models, templates and synthesis models augmented with template information. An evaluation of the multiform segment synthesis technique shows improvements over traditional concatenative methods of synthesis.