Patent Document ID: 20170206892
Application ID: 15407663
Patent Status: 0

Claim One:
1. A method for generating a test-speaker-specific adaptive system for recognising sounds in speech spoken by a test speaker, the method employing: for each of a plurality of training speakers, a respective set of first training data comprising (i) data characterizing speech items spoken by the respective training speaker, and (ii) data characterizing phones for the speech items; and second training data comprising data characterizing speech items spoken by the test speaker; the method comprising: (a) using the sets of first training data to perform supervised learning of a first adaptive model (BN-DNN) comprising (i) an input network component and (ii) an adaptive model component, thereby training the input network component and the adaptive model component; (b) for each of the training speakers: (i) providing a respective second adaptive model comprising (i) the trained input network component, (ii) and a respective training-speaker-specific adaptive model component; and (ii) modifying the training-speaker-specific adaptive model component to perform supervised learning of the respective second adaptive model using the respective set of first training data, thereby producing a respective training-speaker-specific adaptive model component (SDBN-1, SDBN-2,. .. , SDBN-N); (c) training a speaker-adaptive output network, by, successively for each training speaker, modifying the speaker-adaptive output network to train, using the respective set of first training data, a respective third adaptive model comprising the trained input network component, the respective trained training-speaker-specific adaptive model component, and the speaker-adaptive output network; (d) using the second training data to train a test-speaker-specific adaptive model component of a fourth adaptive model comprising the trained input network component, and the test-speaker-specific adaptive model component; and (e) providing the test-speaker-specific adaptive system comprising the trained input network component, the trained test-speaker-specific adaptive model component, and the trained speaker-adaptive output network.