Speaker identification method and speaker identification device
First Claim
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1. A speaker identification method, comprising:
- executing, using a processor, learning mode processing using a first database, in which a plurality of unspecified speakers and a plurality of unspecified speaker models obtained by modeling features of voices of the plurality of unspecified speakers are associated and stored, is used to create a second database, in which first speakers who are not stored in the first database and a plurality of the unspecified speaker models are associated and stored; and
executing, using the processor, identification mode processing in which the second database is used to identify a second speaker,wherein, in the executing of the learning mode processing,a voice signal of each of the first speakers is acquired,first similarity degrees between a feature value in the acquired voice signal of each of the first speakers and each feature value in the plurality of unspecified speaker models stored in the first database are calculated,a plurality of the unspecified speaker models for which the calculated first similarity degrees are equal to or greater than a prescribed value are specified, andeach of the first speakers and the specified plurality of unspecified speaker models are associated and stored in the second database, andin the executing of the identification mode processing,a voice signal of the second speaker is acquired,a plurality of second similarity degrees between a feature value in the acquired voice signal of the second speaker and each feature value in the plurality of unspecified speaker models associated with the first speakers and stored in the second database are calculated for each of the first speakers,the calculated plurality of second similarity degrees are corrected by multiplying each of the plurality of second similarity degrees by a weighting value that corresponds to a ranking of the first similarity degrees,a total value obtained by totaling the corrected plurality of second similarity degrees is calculated for each of the first speakers, andone of the first speakers stored in the second database who corresponds to the second speaker is specified based on the calculated total values.
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Abstract
A first similarity degree processor calculates first similarity degrees between a feature value in voice signal of each of first speakers and each feature value in a plurality of unspecified speaker models of a plurality of unspecified speakers. The processor specifies a plurality of the unspecified speaker models for which the first similarity degrees are equal to or greater than a prescribed value. The processor also associates and stores each of the first speakers and the specified unspecified speaker models. Additionally, the processor calculates, for each of the first speakers, a plurality of second similarity degrees between a feature value in a voice signal of a second speaker and each feature values in the unspecified speaker models associated with the first speakers and stored in a second speaker model storage. The processor further specifies the second speaker based on the second similarity degrees.
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10 Claims
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1. A speaker identification method, comprising:
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executing, using a processor, learning mode processing using a first database, in which a plurality of unspecified speakers and a plurality of unspecified speaker models obtained by modeling features of voices of the plurality of unspecified speakers are associated and stored, is used to create a second database, in which first speakers who are not stored in the first database and a plurality of the unspecified speaker models are associated and stored; and executing, using the processor, identification mode processing in which the second database is used to identify a second speaker, wherein, in the executing of the learning mode processing, a voice signal of each of the first speakers is acquired, first similarity degrees between a feature value in the acquired voice signal of each of the first speakers and each feature value in the plurality of unspecified speaker models stored in the first database are calculated, a plurality of the unspecified speaker models for which the calculated first similarity degrees are equal to or greater than a prescribed value are specified, and each of the first speakers and the specified plurality of unspecified speaker models are associated and stored in the second database, and in the executing of the identification mode processing, a voice signal of the second speaker is acquired, a plurality of second similarity degrees between a feature value in the acquired voice signal of the second speaker and each feature value in the plurality of unspecified speaker models associated with the first speakers and stored in the second database are calculated for each of the first speakers, the calculated plurality of second similarity degrees are corrected by multiplying each of the plurality of second similarity degrees by a weighting value that corresponds to a ranking of the first similarity degrees, a total value obtained by totaling the corrected plurality of second similarity degrees is calculated for each of the first speakers, and one of the first speakers stored in the second database who corresponds to the second speaker is specified based on the calculated total values. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A speaker identification device comprising:
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a processor; and a memory that stores a program, wherein the program causes the processor to execute a learning mode processing using a first database, in which a plurality of unspecified speakers and a plurality of unspecified speaker models obtained by modeling features of voices of the plurality of unspecified speakers are associated and stored, to create a second database, in which first speakers who are not stored in the first database and a plurality of the unspecified speaker models are associated and stored and execute an identification mode processing using the second database to identify a second speaker, wherein, in the execution of the learning mode processing, a voice signal of each of the first speakers is acquired, first similarity degrees between a feature value in the voice signal of each of the first speakers acquired by the first voice acquirer and each feature value in the plurality of unspecified speaker models stored in the first database are calculated, a plurality of the unspecified speaker models for which the first similarity degrees calculated by the first similarity degree calculator are equal to or greater than a prescribed value are specified, and each of the first speakers and the plurality of unspecified speaker models specified by the first specifier in the second database are associated and stored in the second database, and in the execution of the identification mode processing, a voice signal of the second speaker is acquired, a plurality of second similarity degrees between a feature value in the voice signal of the second speaker acquired by the second voice acquirer and each feature value in the plurality of unspecified speaker models associated with the first speakers and stored in the second database are calculated for each of the first speakers, the calculated plurality of second similarity degrees are corrected by multiplying each of the plurality of second similarity degrees by a weighting value that corresponds to a ranking of the first similarity degrees, a total value obtained by totaling the corrected plurality of second similarity degrees is calculated for each of the first speakers, and one of the first speakers stored in the second database who corresponds to the second speaker is specified based on the calculated total values.
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10. A speaker identification method, comprising:
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executing, using a processor, learning mode processing using a first database, in which a plurality of unspecified speakers and a plurality of unspecified speaker models obtained by modeling features of voices of the plurality of unspecified speakers are associated and stored, is used to create a second database, in which first speakers who are not stored in the first database and a plurality of the unspecified speaker models are associated and stored; and executing, using the processor, identification mode processing in which the second database is used to identify a second speaker, wherein, in the executing of the learning mode processing, a voice signal of each of the first speakers is acquired, first similarity degrees between a feature value in the acquired voice signal of each of the first speakers and each feature value in the plurality of unspecified speaker models of a plurality of the unspecified speakers who are different from the first speakers and are stored in the first database are calculated, a plurality of the unspecified speaker models for which the calculated first similarity degrees are equal to or greater than a prescribed value are specified, a speaker model corresponding to each of the first speakers is newly created based on the specified plurality of the unspecified speaker models and the acquired voice signals of the first speakers, and the created speaker model is associated with the first speakers and stored in the second database, and in the executing of the identification mode processing, a voice signal of the second speaker is acquired, a plurality of second similarity degrees between a feature value in the acquired voice signal of the second speaker and feature values in the speaker models associated with the first speakers and stored in the second database are calculated for each of the first speakers, the calculated plurality of second similarity degrees are corrected by multiplying each of the plurality of second similarity degrees by a weighting value that corresponds to a ranking of the first similarity degrees, a total value obtained by totaling the corrected plurality of second similarity degrees is calculated for each of the first speakers, and one of the first speakers stored in the second database who corresponds to the second speaker is specified based on the calculated total values.
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Specification
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Current AssigneePanasonic Corporation (Panasonic Holdings Corporation)
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Original AssigneePanasonic Corporation (Panasonic Holdings Corporation)
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InventorsTsujikawa, Misaki, Matsui, Tomoko
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Primary Examiner(s)Saint Cyr, Leonard
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Application NumberUS15/130,944Publication NumberTime in Patent Office731 DaysField of Search704239, 704246, 704247, 704251, 704252US Class CurrentCPC Class CodesG10L 17/04 Training, enrolment or mode...G10L 17/06 Decision making techniques;...
