Comparison of three approaches to phonetic string generation for large vocabulary speech recognition
Javier Macías-Guarasa, Manuel A. Leandro, Xavier Menéndez-Pidal, José Colás, Ascension Gallardo, José Manuel Pardo, Santiago Aguilera · 1994
We are building a large vocabulary, isolated word preselection system according to a bottom-up design strategy. It will be used in the development of a dictation machine for Spanish and it is composed of three main modules: feature extraction, phonetic string build up and lexical access. In the second one, we are considering three different technological approaches based on static modeling (SM), Hidden Markov Models (HMM) and Neural Networks (NN). This paper will compare these three alternatives in terms of recognition performance, training complexity and computational load, and will conclude with the results of the comparison in order to adopt the most suitable approach depending on the task. I. INTRODUCTION The study we are presenting was done to help the decision process of adopting a certain technology for future developments in very large vocabulary speech recognition systems based in the hypothesisverification paradigm. The stage analyzed here constitutes the first step (hypoth...