IP Library › Patent Application 18038466
Patent Application
App. No. 18/038,466

CONSUMER BEHAVIOR PREDICTION METHOD, CONSUMER BEHAVIOR PREDICTION DEVICE, AND CONSUMER BEHAVIOR PREDICTION PROGRAM

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Patent No.
US None
App. No.
18/038,466
Abstract

An acquisition unit acquires a voice feature quantity vector representing a feature of input voice data, an emotion expression vector representing a customer's emotion corresponding to the voice data, and a purchase intention vector representing a purchase intention of the customer corresponding to the voice data. A learning unit generates, by learning, a purchase intention estimation model for estimating a purchase intention of a customer corresponding to the voice data by using the voice feature quantity vector, the emotion expression vector, and the purchase intention vector.

Claims (20)

1 . A consumer behavior prediction method executed by a consumer behavior prediction device, the method comprising:

an acquisition process of acquiring a voice feature quantity vector representing a feature of input voice data, an emotion expression vector representing a customer's emotion corresponding to the voice data, and a purchase intention vector representing a purchase intention of the customer corresponding to the voice data; and

a learning process of generating, by learning, a model for estimating a purchase intention of a customer corresponding to the voice data by using the voice feature quantity vector, the emotion expression vector, and the purchase intention vector.

2 . The consumer behavior prediction method according to claim 1 , wherein the learning process generates the model by learning by using the emotion expression vector as an intermediate output.

3 . The consumer behavior prediction method according to claim 1 , further comprising: an estimation process of estimating the purchase intention vector corresponding to the input voice data using the generated model.

4 . The consumer behavior prediction method according to claim 1 , wherein the acquisition process uses a model that outputs the emotion expression vector corresponding to the voice feature quantity vector.

5 . The consumer behavior prediction method according to claim 1 , wherein

the acquisition process further acquires a product information vector representing information on a product corresponding to the voice data, and

the learning process generates the model by learning by further using the product information vector.

6 . The consumer behavior prediction method according to claim 1 , wherein

the acquisition process further acquires a customer information vector representing attributes of the customer corresponding to the voice data, and

the learning process generates the model by learning by further using the customer information vector.

7 . A consumer behavior prediction device comprising:

a memory; and

a processor coupled to the memory and programmed to execute a process comprising:

acquiring a voice feature quantity vector representing a feature of input voice data, an emotion expression vector representing a customer's emotion corresponding to the voice data, and a purchase intention vector representing a purchase intention of the customer corresponding to the voice data; and

generating, by learning, a model for estimating a purchase intention of a customer corresponding to the voice data by using the voice feature quantity vector, the emotion expression vector, and the purchase intention vector.

8 . A non-transitory computer-readable recording medium having stored a consumer behavior prediction program for causing a computer to execute

an acquisition step of acquiring a voice feature quantity vector representing a feature of input voice data, an emotion expression vector representing a customer's emotion corresponding to the voice data, and a purchase intention vector representing a purchase intention of the customer corresponding to the voice data, and

a learning step of generating, by learning, a model for estimating a purchase intention of a customer corresponding to the voice data by using the voice feature quantity vector, the emotion expression vector, and the purchase intention vector.

Assignments (2)
CHANGE OF NAME Recorded Oct 3, 2025
From: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
To: NTT, INC.
Reel/Frame 073007/0308 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 24, 2023
From: NAGANO, MIZUKI; IJIMA, YUSUKE
To: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Reel/Frame 063742/0447 →