Name segmentation using hidden Markov models and its application in record linkage

Preparation of name and address data for record linkage using hidden Markov models

BACKGROUND Record linkage refers to the process of joining records that relate to the same entity or event in one or more data collections. In the absence of a shared, unique key, record linkage involves the comparison of ensembles of partially-identifying, non-unique data items between pairs of records. Data items with variable formats, such as names and addresses, need to be transformed and n...

Joint segmentation and image interpretation using hidden Markov models

Image interpretation consists of interleaving the low-level task of image segmentation and the high-level task of interpretation. The idea being that the interpretation block guides the segmentation block which in turn helps the interpretation block in better interpretation. In this paper, we develop a joint segmentation and image interpretation scheme using the notion of joint hidden Markov mo...

Story Segmentation Using Social Network Analysis and Hidden Markov Models

Chord segmentation and recognition using EM-trained hidden markov models

Automatic extraction of content description from commercial audio recordings has a number of important applications, from indexing and retrieval through to novel musicological analyses based on very large corpora of recorded performances. Chord sequences are a description that captures much of the character of a piece in a compact form and using a modest lexicon. Chords also have the attractive...

Face Segmentation For Identification Using Hidden Markov Models

This paper details work done on face processing using a novel approach involving Hidden Markov Models. Experimental results from earlier work [14] indicated that left-to-right models with use of structural information yield better feature extraction than ergodic models. This paper illustrates how these hybrid models can be used to extract facial bands and automatically segment a face image into...