Advanced New Technologies Co., Ltd.

Alipay (Hangzhou) Information Technology Co., Ltd.

Kaisheng Yao

Xiaolong Li

Zhiming Wang

Peng Xu

Xiaofu Chang

Yuan Qi

Jiaxing Zhang

Jia Liu

Data storage and calling methods and devices are provided. One of the methods includes: receiving first motion data and business data; establishing an association relationship between the first motion data and the business data and storing the association relationship; receiving second motion data; and determining first motion data that matches the second motion data, and returning, to a sender of the second motion data, business data associated with the matched first motion data.

Data storage and calling methods and devices

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining voice characteristics are provided. One of the methods includes: obtaining speech data of a speaker; inputting the speech data into a model trained at least by jointly minimizing a first loss function and a second loss function, wherein the first loss function comprises a non-sampling-based loss function and the second loss function comprises a Gaussian mixture loss function with non-unit multi-variant covariance matrix; and obtaining from the trained model one or more voice characteristics of the speaker.

System and method for determining voice characteristics

Implementations of the present specification provide a method and an apparatus for extending question and answer samples. According to the method, a random number is generated for each existing sample, a question is blurred for a sample whose random number belongs to sample extension random numbers, to generate an extended sample, so that an overall sample blurring extension rate can be effectively controlled. In addition, for a sample needing blurring extension, a question is extended by deleting a word with a predetermined part of speech in the corresponding question, and then an extended sample is generated based on an extended question, so that more question expression ways are compatible. As such, a question and answer model is trained by using a sample set to which extended samples are added, so that an answer can be provided to a user more effectively.

Extending question and answer samples

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for personalized speaker verification are provided. One of the methods includes: obtaining first speech data of a speaker as a positive sample and second speech data of an entity different from the speaker as a negative sample; feeding the positive sample and the negative sample to a first model for determining voice characteristics to correspondingly output a positive voice characteristic and a negative voice characteristic of the speaker; obtaining a gradient based at least on the positive voice characteristic and the negative voice characteristic; and feeding the gradient to the first model to update one or more parameters of the first model to obtain a second model for personalized speaker verification.

System and method for personalized speaker verification

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining voice characteristics are provided. One of the methods includes: obtaining speech data of a speaker; inputting the speech data into a model trained at least by jointly minimizing a first loss function and a second loss function, wherein the first loss function comprises a non-sampling-based loss function and the second function comprises a Gaussian mixture loss function with non-unit multi-variant covariance matrix; and obtaining from the trained model one or more voice characteristics of the speaker.

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Hangzhou, China

Kaisheng Yao