Speaker verification based on a speaker template

A method of speaker verification, the method comprising:

• determining, at a device, a first feature vector based on a first utterance;
• determining, at the device, a first embedding vector based on the first feature vector by processing the first feature vector using a trained embedding network;
• determining, at the device, a first distance metric based on distances between the first embedding vector and each embedding vector of a speaker template associated with a particular user, the speaker template including one or more enrollment embedding vectors based on initial user enrollment data and including one or more test embedding vectors;
• determining, at the device, that the first utterance is verified to be from the particular user based on determining that the first distance metric satisfies a speaker verification threshold;
• based on determining that the first utterance is verified to be from the particular user, performing a comparison of a first particular distance metric associated with the first embedding vector to a second distance metric associated with a first test embedding vector of the speaker template;
• and
• based on the comparison, generating an updated speaker template by adding the first embedding vector as a second test embedding vector and removing the first test embedding vector from the test embedding vectors of the speaker template.

A computer-readable storage device storing instructions that, when executed by a processor, cause the processor to perform operations comprising:

• determining a first feature vector based on a first utterance;
• determining a first embedding vector based on the first feature vector by processing the first feature vector using a trained embedding network;
• determining a first distance metric based on distances between the first embedding vector and each embedding vector of a speaker template associated with a particular user, the speaker template including one or more enrollment embedding vectors based on initial user enrollment data and including one or more test embedding vectors;
• performing a speaker verification operation to determine, based on the first distance metric, whether the first utterance is verified to be from the particular user;
• based on determining that the first utterance is verified to be from the particular user, performing a comparison of a first particular distance metric associated with the first embedding vector to a second distance metric associated with a first test embedding vector of the speaker template;
• and
• based on the comparison, generating an updated speaker template by adding the first embedding vector as a second test embedding vector and removing the first test embedding vector from the test embedding vectors of the speaker template.

An apparatus comprising:

• means for storing a trained embedding network;
• means for storing a speaker template associated with a particular user, the speaker template including one or more enrollment embedding vectors based on initial user enrollment data and including one or more test embedding vectors;
• means for determining a first feature vector based on a first utterance;
• means for determining a first embedding vector based on the first feature vector by processing the first feature vector using the trained embedding network;
• means for determining a first distance metric based on distances between the first embedding vector and each embedding vector of the speaker template;
• means for performing a speaker verification operation to determine, based on the first distance metric, whether the first utterance is verified to be from the particular user;
• means for performing a comparison of a first particular distance metric associated with the first embedding vector to a second distance metric associated with a first test embedding vector of the speaker template, the comparison performed based on determining that the first utterance is verified to be from the particular user;
• and
• means for generating an updated speaker template by adding the first embedding vector as a second test embedding vector and removing the first test embedding vector from the test embedding vectors of the speaker template, the updated speaker template generated based on the comparison.