WO-2026095582-A1 - MACHINE LEARNING-BASED INPUT DEVICE, INPUT SYSTEM, AND METHOD FOR PROCESSING INPUT

WO2026095582A1WO 2026095582 A1WO2026095582 A1WO 2026095582A1WO-2026095582-A1

Abstract

In one embodiment, provided may be a machine learning-based input device which is coupled to or in contact with an object that serves as a medium for transmitting sound, the input device comprising: a sound reception unit for acquiring the sound as an input signal via the object, and electrically converting the input signal; a processing unit for receiving the input signal from the sound reception unit, and inputting sound data corresponding to the input signal into a pre-trained learning model so as to output a command corresponding to the sound data; and a signal generation unit for generating a control signal for executing the command.

Inventors

PARK, JUNYOUNG
LEE, Seonae
LEE, Takgeon

Assignees

주식회사 커먼링크

Dates

Publication Date: 20260507
Application Date: 20251028
Priority Date: 20241028

Claims (12)

In an input device coupled to or in contact with an object that serves as a medium for transmitting sound, A sound receiving unit that acquires the above sound as an input signal through the above object and electrically converts the input signal; A processing unit that receives the input signal from the sound receiving unit, inputs sound data corresponding to the input signal into a pre-trained learning model, and outputs a command corresponding to the sound data; and A signal generation unit comprising a signal generating unit for generating a control signal to execute the above command Machine learning-based input device.
In paragraph 1, The above sound is generated when the surface of the object is stimulated and is transmitted to the sound receiving unit through the object. Machine learning-based input device.
In paragraph 2, The above stimulus is electrical or non-electric, and The above object is composed of a conductive material or a non-conductive material. Machine learning-based input device.
In paragraph 1, The above learning model is composed of an artificial neural network including an RNN (recurrent neural network) or a CNN (convolutional neural network). Machine learning-based input device.
In paragraph 4, The above learning model is composed of a combination of an RNN artificial neural network and a CNN artificial neural network. Machine learning-based input device.
In paragraph 1, The above learning model includes a plurality of learning models, and The processing unit outputs the command based on the output results of the plurality of learning models for the sound data. Machine learning-based input device.
In paragraph 1, The above sound receiving unit includes a plurality of sound receiving units that each acquire the sound as an input signal through the object and electrically convert the plurality of input signals. A plurality of input signals are received from the plurality of sound receivers, and a plurality of sound data corresponding to the plurality of input signals are input into the learning model to output a single command corresponding to the plurality of sound data. Machine learning-based input device.
In paragraph 1, It includes a communication unit that communicates by being connected to an electronic device via a wired or wireless network and transmits the control signal to the electronic device. The above control signal controls the electronic device so that the electronic device executes the above command. Machine learning-based input device.
Input device according to paragraph 1; and It includes an object to which the above-mentioned input device is coupled on one side, and The above sound is generated when the surface of the object is stimulated and is transmitted to the sound receiving unit through the object. Machine learning-based input system.
A method for processing input in an input device coupled to an object as a medium for transmitting sound, A step of acquiring the above sound as an input signal through the above object; A step of electrically converting the above input signal; A step of generating a command corresponding to the input signal from the input signal, wherein the input signal is received, sound data corresponding to the input signal is input into a pre-trained learning model to output a command corresponding to the sound data; and A step comprising generating a control signal for executing the above command A method for processing input based on machine learning.
In Paragraph 10, The above sound is generated when the surface of the object is stimulated and is transmitted to the sound receiving unit through the object. A method for processing input based on machine learning.
A computer-readable medium storing a program that performs the method of paragraph 10.

Description

Machine learning-based input device, input system, and method for processing input The present embodiment relates to an input device for processing sound signals, and to a technology for processing input based on machine learning. Generally, mechanical and/or electronic devices are equipped with input devices. Simply put, switches or buttons are primarily used, while keyboards, touchscreens, touchpads, trackballs, or mice are used to implement complex functions. However, conventional input devices have various limitations. For example, since input devices must be indispensably installed somewhere within an electronic device or a product containing it, they impose constraints such as compromising the design or requiring compatibility with other internal components. Furthermore, because conventional input devices must be operated by a user, they are exposed to the outside of the product; in this case, they may malfunction or break down due to exposure to moisture, temperature, or foreign substances. To solve these problems, there is an urgent need to develop a new concept of input device that is robust against external environments, provides a simple input method, and is compatible with any other device. Accordingly, the inventor of the present invention has completed the present invention after a long period of research and trial and error. FIG. 1 is a configuration diagram of an input device according to one embodiment. FIG. 2 is an illustrative diagram for explaining the use of an input device according to one embodiment. FIG. 3 is a drawing showing an example of an input device according to one embodiment. FIG. 4 is a drawing showing another example of an input device according to one embodiment. FIG. 5 is an example of sound data input to an input device according to one embodiment. FIG. 6 is an example of preprocessed sound data of sound data input to an input device according to one embodiment. FIG. 7 is an example diagram of a learning model of an input device according to one embodiment. FIG. 8 is another example of a learning model of an input device according to one embodiment. FIG. 9 is another example of a learning model of an input device according to one embodiment. FIG. 10 is a flowchart of an operation in which an input device according to one embodiment processes input through a learning model. FIG. 11 is a flowchart of an operation in which an input device according to one embodiment processes input through a plurality of learning models. FIG. 12 is a diagram illustrating the operation of an input device according to one embodiment processing input through a plurality of learning models. FIG. 13 is a flowchart of an operation in which an input device according to one embodiment processes a plurality of inputs through a learning model. FIG. 14 is an example of a plurality of sound data input to an input device according to one embodiment. It should be noted that the attached drawings are provided as examples for reference to help understand the technical concept of the present invention, and the scope of the rights of the present invention is not limited by them. In describing the present invention, detailed descriptions of related known functions are omitted if they are deemed obvious to a person skilled in the art and could unnecessarily obscure the essence of the invention. The terms used in this application are used merely to describe specific embodiments and are not intended to limit the invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as "comprising" or "having" are intended to specify the presence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. Terms such as "first," "second," etc. are merely identifiers for distinguishing identical or corresponding components, and identical or corresponding components are not limited by terms such as "first," "second," etc. Hereinafter, embodiments according to the present invention will be described in detail with reference to the accompanying drawings. In describing with reference to the accompanying drawings, identical or corresponding components are given the same reference numerals, and redundant descriptions thereof will be omitted. FIG. 1 is a configuration diagram of an input device according to one embodiment, and FIG. 2 is an example diagram for explaining the use of an input device according to one embodiment. An input device (100) according to one embodiment has the primary purpose of processing input and may provide some operation or result as an auxiliary function after processing the input. This is because the input device (100) is specialized in processing input provided by a user in the form of sound. In