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US 6,212,500 B1Granted
Process for the multilingual use of a hidden markov sound model in a speech recognition system
AssigneeSiemens Aktiengesellschaft
InventorJoachim Köhler
Life of this patent
Estimating the term…
Abstract
In a method for determining the similarities of sounds across different languages, hidden Markov modelling of multilingual phonemes is employed wherein language-specific as well as language-independent properties are identified by combining of the probability densities for different hidden Markov sound models in various languages.
Claims9
A method for modelling a sound in at least two languages, comprising the steps of:
- (a) identifying a first feature vector for a first spoken sound in a first language;
- (b) identifying a first hidden Markov sound model, from among a plurality of standard Markov sound models in a Markov sound model library, which most closely models said first feature vector;
- (c) identifying a second feature vector for a second spoken sound, comparable to said first spoken sound, in a second language;
- (d) identifying a second hidden Markov sound model from among said plurality of standard Markov sound models in said Markov sound model library, which most closely models said second feature vector;
- (e) employing a predetermined criterion to select one of said first and second hidden Markov sound models as better modelling both of said first and second feature vectors;
- and
- (f) modelling said first and second spoken sounds in both of said first and second languages using said one of said first and second hidden Markov sound models.
4 more elements
A method for multilingual employment of a hidden Markov sound model in a speech recognition system, comprising the steps of:
- (a) identifying a first hidden Markov sound model for a first spoken sound in a first language, said first hidden Markov sound model having a first standard probability distribution associated therewith;
- (b) identifying a second hidden Markov sound model for a second spoken sound, comparable to said first spoken sound, in a second language, said second hidden Markov sound model having a second standard probability distribution associated therewith;
- (c) combining said first standard probability distribution and said second standard probability distribution to form a new standard probability distribution up to a defined distance threshold, said defined distance threshold identifying a maximum distance between said first and second probability distributions within which said first and second standard probability distributions should be combined;
- (d) forming a polyphoneme model using said new standard probability distribution only within said defined distance threshold and modelling said first and second sounds in both of said first and second languages using said polyphoneme model.
1 more element
Dependencies are inferred from the claim text.