×

Method for recognizing speech using linguistically-motivated hidden Markov models

  • US 5,581,655 A
  • Filed: 01/22/1996
  • Issued: 12/03/1996
  • Est. Priority Date: 01/31/1991
  • Status: Expired due to Term
First Claim
Patent Images

1. A method for estimating pronunciation probabilities in word pronunciation networks that incorporate dialectal variations in pronunciation for use in a speech recognition system wherein said word networks comprise a plurality of nodes, each node connected to its successive node by one or more arcs, each arc having associated with it a phone and a numerical variable for storing the pronunciation probability that arc is taken comprising the steps of:

  • determining equivalence classes for a plurality of nodes in the word pronunciation networks by;

    if context with surrounding nodes is not relevant phone choice at a node, classifying that node with nodes having similar phone choices into the same equivalence class; and

    if context with surrounding nodes is important in determining phone choice at a node, classifying that node in an equivalence class with similar nodes having similar phone choices and sharing identical relevant contextual constraints, such that all nodes in the same equivalence class may share training samples for estimating pronunciation probabilities; and

    using a set of training samples to estimate the pronunciation probabilities in the word pronunciation network such that training samples for a given word will contribute to the training of networks for all other words that have any nodes in an equivalence class with any of the nodes of that word.

View all claims
  • 0 Assignments
Timeline View
Assignment View
    ×
    ×