Publications by Fiona Couper Kenney

s0129866.bib

@mastersthesis{Couper-02,
  author = {Couper, Fiona},
  title = {Switching linear dynamical models for automatic speech
                   recognition},
  school = {University of Edinburgh},
  abstract = {The field of speech recognition research has been
                   dominated by the Hidden Markov Model (HMM) in recent
                   years. The HMM has known weaknesses, such as the strong
                   ``independence assumption'' which presumes observations
                   to be uncorrelated. New types of statistical modelling
                   are now being investigated to overcome the weaknesses
                   of HMMs. One such model is the Linear Dynamical Model
                   (LDM), whose properties are more appropriate to speech.
                   Modelling phone segments with LDMs gives fairly good
                   classification and recognition scores, and this report
                   explores possible extensions to a system using such
                   models. Training only one model per phone cannot fully
                   model variation that exists in speech, and perhaps
                   training more than one model for some segments will
                   improve accuracy scores. This is investigated here, and
                   four methods for building two models instead of one for
                   any phone are presented. Three of the methods produce
                   significantly increased classification accuracy scores,
                   compared to a set of single models.},
  categories = {asr},
  pdf = {http://www.cstr.ed.ac.uk/downloads/publications/2002/couper_msc.pdf},
  year = 2002
}