US 2014/0195236 A1 · SPEAKER VERIFICATION AND IDENTIFICATION USING ARTIFICIAL NEURAL NETWORK-BASED SUB-PHONETIC UNIT DISCRIMINATION

Abstract

In one embodiment, a computer system stores speech data for a plurality of speakers, where the speech data includes a plurality of feature vectors and, for each feature vector, an associated sub-phonetic class. The computer system then builds, based on the speech data, an artificial neural network (ANN) for modeling speech of a target speaker in the plurality of speakers, where the ANN is configured to discriminate between instances of sub-phonetic classes uttered by the target speaker and instances of sub-phonetic classes uttered by other speakers in the plurality of speakers.

Claims20

Dependent claims

A method comprising:

storing, by a computer system, speech data for a plurality of speakers, the speech data including a plurality of feature vectors and, for each feature vector, an associated sub-phonetic class;
and
building, by the computer system based on the speech data, an artificial neural network (ANN) for modeling speech of a target speaker in the plurality of speakers, the ANN being configured to discriminate between instances of sub-phonetic classes uttered by the target speaker and instances of sub-phonetic classes uttered by other speakers in the plurality of speakers.

A non-transitory computer readable storage medium having stored thereon program code executable by a computer system, the program code comprising:

code that causes the computer system to store speech data for a plurality of speakers, the speech data including a plurality of feature vectors and, for each feature vector, an associated sub-phonetic class;
and
code that causes the computer system to build, based on the speech data, an artificial neural network (ANN) for modeling speech of a target speaker in the plurality of speakers, the ANN being configured to discriminate between instances of sub-phonetic classes uttered by the target speaker and instances of sub-phonetic classes uttered by other speakers in the plurality of speakers.

A system comprising:

a processor configured to:
store speech data for a plurality of speakers, the speech data including a plurality of feature vectors and, for each feature vector, an associated sub-phonetic class;
and
build, based on the speech data, an artificial neural network (ANN) for modeling speech of a target speaker in the plurality of speakers, the ANN being configured to discriminate between instances of sub-phonetic classes uttered by the target speaker and instances of sub-phonetic classes uttered by other speakers in the plurality of speakers.

1 more element

Dependencies are inferred from the claim text.

Facts

Application

13/738,868Filed 10 Jan 2013

Published

10 Jul 2014

Term ends

Not estimatedThe source records don’t support an estimate.

Classification7 codes

G10L 17/14
Decision making techniques; Pattern matching strategies: use of phonemic categorisation or speech recognition prior to speaker recognition or…
G06N 3/082
Learning methods: modifying the architecture, e.g. adding, deleting or silencing nodes or connections
G06N 3/084
Learning methods: backpropagation, e.g. using gradient descent
G10L 17/04
Speaker identification or verification techniques: training, enrolment or model building

Speaker verification and identification using artificial neural network-based sub-phonetic unit discrimination

Life of this patent

Speaker verification and identification using artificial neural network-based sub-phonetic unit discrimination

Life of this patent

Abstract

Claims20