Repeated Observation Models

Repetition is an important phenomenon in a variety of domains, such as music, computer programs and architectural drawings. A generative model for these domains should account for the possibility of repetition. We present repeated observation models (ROMs), a framework for modeling sequences that explicitly allows for repetition. In a ROM, an element is either generated by copying a previous element, or by using a base model. We show how to build ROMs using grams and hidden Markov models as the base model. We also describe an extension of ROMs in which entire subsequences are repeated together. Results from a music modeling domain show that ROMs can lead to dramatic improvement in predictive ability.

• Type: Conference
• Year: 2004
• Where: AAAI
• Authors: Avi Pfeffer
• Keywords: AAAI 2004, Base Model, Hidden Markov Models, Intelligent Agents, ROMs