Selection of alternative word sequences for discriminative adaptation
First Claim
1. A method for the discriminative adaptation of acoustic reference models of a speech recognition system, wherein, starting from a set of given acoustic speech signals whose corresponding spoken word sequences are known in each case, and starting from given acoustic reference models, a first scored word sequence is generated for one of the given acoustic speech signals each time through the use of the given acoustic reference models, if said first word sequence differs from the spoken word sequence, said first word sequence is assigned as an alternative word sequence to the spoken word sequence, if not, a second scored word sequence is generated for the given acoustic speech signal through the use of the given acoustic reference models, and, provided the difference between the scores of the first and the second word sequence is smaller than a first threshold value, said second word sequence is assigned as an alternative word sequence to the spoken word sequence, an adaptation of at least one of the given acoustic reference models is carried out with the use of the assignation/assignations thus determined.
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Abstract
The invention relates to a method for the discriminative adaptation of reference models of a pattern recognition system, in particular of acoustic reference models of a speech recognition system, wherein, starting from a quantity of given patterns whose classification is known in each case or is estimated, and starting from given reference models,
a first scored classification is generated for one of the given patterns through the use of the given reference models,
if said first classification differs from the known or estimated classification, said first classification is assigned as an alternative classification to the known or estimated classification,
if not, a second scored classification is generated for the given pattern with the use of the given reference models and, provided the difference between the scores of the first and second classifications is smaller than a first threshold value, said second classification is assigned as an alternative classification to the known or estimated classification,
an adaptation of at least one of said given reference models is carried out with the use of the assignation/assignations thus determined.
42 Citations
14 Claims
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1. A method for the discriminative adaptation of acoustic reference models of a speech recognition system, wherein, starting from a set of given acoustic speech signals whose corresponding spoken word sequences are known in each case, and starting from given acoustic reference models,
a first scored word sequence is generated for one of the given acoustic speech signals each time through the use of the given acoustic reference models, if said first word sequence differs from the spoken word sequence, said first word sequence is assigned as an alternative word sequence to the spoken word sequence, if not, a second scored word sequence is generated for the given acoustic speech signal through the use of the given acoustic reference models, and, provided the difference between the scores of the first and the second word sequence is smaller than a first threshold value, said second word sequence is assigned as an alternative word sequence to the spoken word sequence, an adaptation of at least one of the given acoustic reference models is carried out with the use of the assignation/assignations thus determined.
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7. A method for the discriminative adaptation of acoustic reference models of a speech recognition system, wherein, starting from a set of given acoustic speech signals whose corresponding spoken word sequences are known or estimated in each case, and starting from given acoustic reference models,
a first scored word sequence is generated for one of the given acoustic speech signals each time through the use of the given acoustic reference models, if said first word sequence differs from the known or estimated word sequence, said first word sequence is assigned as an alternative word sequence to the known or estimated word sequence, if not, a second scored word sequence is generated for the given acoustic speech signal through the use of the given acoustic reference models, and, provided the difference between the scores of the first and the second word sequence is smaller than a first threshold value, said second word sequence is assigned as an alternative word sequence to the known or estimated word sequence, an adaptation of at least one of the given acoustic reference models is carried out with the use of the assignation/assignations thus determined.
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11. A method for the discriminative adaptation of reference models of a pattern recognition system wherein, starting from a quantity of given patterns whose classification is known in each case or is estimated, and starting from given reference models,
a first scored classification is generated for one of the given patterns through the use of the given reference models, if said first classification differs from the known or estimated classification, said first classification is assigned as an alternative classification to the known or estimated classification, if not, a second scored classification is generated for the given pattern with the use of the given reference models and, provided the difference between the scores of the first and second classifications is smaller than a first threshold value, said second classification is assigned as an alternative classification to the known or estimated classification, an adaptation of at least one of said given reference models is carried out with the use of the assignation/assignations thus determined.
Specification
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- Resources
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Current AssigneeKoninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
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Original AssigneeKoninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
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InventorsMeyer, Carsten
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Application NumberUS09/982,285Publication NumberTime in Patent OfficeDaysField of SearchUS Class Current704/251CPC Class CodesG10L 15/06 Creation of reference templ...G10L 15/063 TrainingG10L 15/075 supervised, i.e. under mach...G10L 15/187 Phonemic context, e.g. pron...G10L 2015/0631 Creating reference template...G10L 2015/0635 updating or merging of old ...
