Electronic devices and methods of processing user utterances

Abstract

An electronic device according to an embodiment is provided. The electronic device may comprise a memory for storing one or more computer programs. The electronic device may include one or more processors communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to instruct the electronic device to receive a user's utterance. The computer-executable instructions may be executed by the one or more processors to instruct the electronic device to analyze the bias of the utterance or the bias of the user. The computer-executable instructions may be executed by the one or more processors to instruct the electronic device to generate a response including biased information on the basis of the result of analyzing bias in the utterance or the result of analyzing bias in the user. The computer-executable instructions may be executed by the one or more processors to instruct the electronic device to provide the response to the user.

Description

Electronic devices and methods for processing user speech

[0001] Embodiments of the present invention relate to an electronic device and a method for processing user speech.

[0002] Electronic devices equipped with voice assistant functions that provide services based on user utterances are becoming increasingly widespread. These devices can recognize user utterances and understand their meaning and intent through an AI server. The AI ​​server can interpret the user's utterances, infer the user's intent, and perform tasks based on this inferred intent. The AI ​​server can then perform tasks based on the user's intent expressed through natural language interaction between the user and the AI ​​server.

[0003] When an AI server provides responses to users based on voice assistant functionality, potential bias and discrimination in the responses are sensitive topics. Therefore, most language model-based question-answering systems are designed to eliminate potential bias in their responses.

[0004] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art related to the present disclosure.

[0005] Aspects of the present disclosure address at least the problems and / or disadvantages described above, and provide at least the advantages described below. Accordingly, aspects of the present disclosure provide an electronic device and a method for processing user speech.

[0006] Additional aspects will be disclosed in part in the following description, and in part will be apparent from the description or may be learned by practice of the embodiments presented.

[0007] An electronic device according to one embodiment is provided. The electronic device may include a memory storing one or more computer programs. The electronic device may include one or more processors communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to analyze the bias of the speech or the user's bias. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response including biased information based on the result of the bias analysis of the speech or the result of the bias analysis of the user. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the response to the user.

[0008] A method of operating an electronic device according to one embodiment is provided. The method may include receiving a user's speech. The method may include analyzing the bias of the speech or the user's bias. The method may include generating a response including biased information based on the results of the bias analysis of the speech or the user's bias. The method may include providing the response to the user.

[0009] An electronic device according to one embodiment is provided. The electronic device may include a memory storing one or more computer programs. The electronic device may include one or more processors communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response including biased information based on the speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate information about a bias of the response based on the response. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the user with the information about the bias and the response together.

[0010] A method of operating an electronic device according to one embodiment is provided. The method may include receiving a user's speech. The method may include generating a response including biased information based on the speech. The method may include generating information about the bias of the response based on the response. The method may include providing the user with the information about the bias and the response together.

[0011] An electronic device according to one embodiment is provided. The electronic device may include a memory storing one or more computer programs. The electronic device may include one or more processors communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's utterance. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to obtain first information about a bias of the utterance or second information about a bias of the user. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a prompt based on the first information or the second information. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response from the prompt that includes biased information based on a general language model or a biased language model. The computer execution instructions may be executed by the one or more processors to cause the electronic device to provide the response to the user.

[0012] A method of operating an electronic device according to one embodiment is provided. The method may include an operation of receiving a user's utterance. The method may include an operation of obtaining first information about a bias of the utterance or second information about the user's bias. The method may include an operation of generating a prompt based on the first information or the second information. The method may include an operation of generating a response including biased information from the prompt based on a general language model or a biased language model. The method may include an operation of providing the response to the user.

[0013] According to one embodiment, one or more non-transitory computer-readable storage media are provided storing one or more computer programs including computer-executable instructions that are executed by one or more processors of an electronic device to cause the electronic device to perform operations. The operations may include receiving a user's utterance. The operations may include analyzing a bias of the utterance or a bias of the user. The operations may include generating a response including biased information based on a result of analyzing the bias of the utterance or a result of analyzing the bias of the user.

[0014] Other aspects, advantages and salient features of the present disclosure will become apparent to those skilled in the art from the following detailed description of various embodiments of the present disclosure taken in conjunction with the accompanying drawings.

[0015] FIG. 1 is a block diagram of an electronic device within a network environment, according to one embodiment.

[0016] FIG. 2 is a block diagram illustrating an integrated intelligence system according to one embodiment.

[0017] FIG. 3 is a diagram showing a form in which relationship information between concepts and actions is stored in a database according to one embodiment.

[0018] FIG. 4 is a diagram illustrating a screen for processing voice input received through an intelligent app by an electronic device according to one embodiment.

[0019] FIG. 5 is a diagram illustrating an operation of an electronic device processing a user's speech according to one embodiment.

[0020] FIG. 6 is a schematic block diagram of an electronic device according to one embodiment.

[0021] FIG. 7 is a diagram for explaining information about bias according to one embodiment.

[0022] FIGS. 8 to 12 are diagrams illustrating an operation of an electronic device processing a user's speech according to one embodiment.

[0023] FIG. 13 illustrates a flowchart of a method of operating an electronic device according to one embodiment.

[0024] The same part number is used throughout the drawing to represent the same component.

[0025] The following description, with reference to the accompanying drawings, is provided to facilitate a comprehensive understanding of various embodiments of the present invention as defined by the claims and their corresponding claims. While numerous specific details are included herein to facilitate this understanding, they are to be considered merely exemplary. Accordingly, those skilled in the art will recognize that various modifications and variations can be made to the various embodiments described herein without departing from the scope and spirit of the present disclosure. Furthermore, descriptions of well-known functions and structures may be omitted for clarity and brevity.

[0026] The terms and words used in the following description and claims are not limited to their bibliographical meanings, but are merely used by the inventors to facilitate a clear and consistent understanding of the present invention. Therefore, it will be apparent to those skilled in the art that the following description of various embodiments of the present disclosure is provided for illustrative purposes only and is not intended to limit the present disclosure as defined by the appended claims and their equivalents.

[0027] Unless the context clearly dictates otherwise, the singular forms "a," "an," and "the" should be understood to include the plural. Thus, for example, reference to "a component surface" includes reference to one or more of such surfaces.

[0028] It should be understood that the blocks and combinations of flowcharts in each flowchart can be performed by one or more computer programs containing instructions. One or more computer programs may be stored entirely in a single memory device, or one or more computer programs may be divided into different parts stored in multiple different memory devices.

[0029] Any function or operation described herein may be processed by a single processor or a combination of processors. A single processor or a combination of processors is a circuit that performs processing, and is an application processor (AP) (e.g., a central processing unit (CPU)), a communication processor (CP) (e.g., a modem), a graphics processing unit (GPU)), a neural processing unit (NPU) (e.g., an artificial intelligence (AI) chip), a Wi-Fi chip, a Bluetooth® chip, a global positioning system (GPS) chip, a near field communication (NFC) chip, a connectivity chip, a sensor controller, a touch controller, a fingerprint sensor controller, a display driver integrated circuit (IC), an audio codec chip, a universal serial bus (USB) controller, a camera controller, an image processing IC, a microprocessor unit (MPU), a system on a chip (SoC), an IC, or a similar chip.

[0030]

[0031] FIG. 1 is a block diagram of an electronic device (101) within a network environment (100) according to one embodiment. Referring to FIG. 1 , in the network environment (100), the electronic device (101) may communicate with the electronic device (102) via a first network (198) (e.g., a short-range wireless communication network), or may communicate with at least one of the electronic device (104) and the server (108) via a network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) via the server (108). According to one embodiment, the electronic device (101) may include a processor (120), a memory (130), an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a connection terminal (178), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197). In some embodiments, the electronic device (101) may omit at least one of these components (e.g., the connection terminal (178)), or may have one or more other components added. In some embodiments, some of these components (e.g., the sensor module (176), the camera module (180), or the antenna module (197)) may be integrated into one component (e.g., the display module (160)).

[0032] The processor (120) may, for example, execute software (e.g., a program (140)) to control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) and perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (120) may store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the commands or data stored in the volatile memory (132), and store result data in a non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or an auxiliary processor (123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together with the main processor (121). For example, when the electronic device (101) includes the main processor (121) and the auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a given function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as a part thereof.

[0033] The auxiliary processor (123) may control at least a portion of functions or states associated with at least one component (e.g., a display module (160), a sensor module (176), or a communication module (190)) of the electronic device (101), for example, on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (180) or a communication module (190)). In one embodiment, the auxiliary processor (123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (108)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0034] The memory (130) can store various data used by at least one component (e.g., processor (120) or sensor module (176)) of the electronic device (101). The data can include, for example, software (e.g., program (140)) and input data or output data for commands related thereto. The memory (130) can include volatile memory (132) or non-volatile memory (134).

[0035] The program (140) may be stored as software in the memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0036] The input module (150) can receive commands or data to be used in a component of the electronic device (101) (e.g., a processor (120)) from an external source (e.g., a user) of the electronic device (101). The input module (150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0037] The audio output module (155) can output audio signals to the outside of the electronic device (101). The audio output module (155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0038] The display module (160) can visually provide information to an external party (e.g., a user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling the device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch.

[0039] The audio module (170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150), output sound through the sound output module (155), or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (101).

[0040] The sensor module (176) can detect the operating status (e.g., power or temperature) of the electronic device (101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0041] The interface (177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (101) with an external electronic device (e.g., the electronic device (102)). In one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0042] The connection terminal (178) may include a connector through which the electronic device (101) may be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0043] The haptic module (179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. According to one embodiment, the haptic module (179) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0044] The camera module (180) can capture still images and videos. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0045] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

[0046] A battery (189) may power at least one component of the electronic device (101). In one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0047] The communication module (190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may operate independently from the processor (120) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (194) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, the corresponding communication module can communicate with an external electronic device (104) via a first network (198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (199) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules can be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can verify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (196).

[0048] The wireless communication module (192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (192) can support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), an external electronic device (e.g., the electronic device (104)), or a network system (e.g., the second network (199)). According to one embodiment, the wireless communication module (192) can support a peak data rate (e.g., 20 Gbps or more) for eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization.

[0049] The antenna module (197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (198) or the second network (199), may be selected from the plurality of antennas, for example, by the communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device via the at least one selected antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (197).

[0050] In one embodiment, the antenna module (197) may form a mmWave antenna module. In one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0051] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0052] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) via a server (108) connected to a second network (199). Each of the external electronic devices (102 or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations executed in the electronic device (101) may be executed in one or more of the external electronic devices (102, 104, or 108). For example, when the electronic device (101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (101) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server utilizing machine learning and / or a neural network. According to one embodiment, the external electronic device (104) or the server (108) may be included in the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0053]

[0054] FIG. 2 is a block diagram illustrating an integrated intelligence system according to one embodiment.

[0055] Referring to FIG. 2, an integrated intelligent system (20) of one embodiment may include an electronic device (201) (e.g., electronic device (101) of FIG. 1), an intelligent server (200) (e.g., server (108) of FIG. 1), and a service server (300) (e.g., server (108) of FIG. 1).

[0056] The electronic device (201) of one embodiment may be a terminal device (or electronic device) that can connect to the Internet, and may be, for example, a mobile phone, a smart phone, a personal digital assistant (PDA), a laptop computer, a TV, white goods, a wearable device, an HMD, or a smart speaker.

[0057] According to the illustrated embodiment, the electronic device (201) may include a communication interface (202) (e.g., the interface (177) of FIG. 1), a microphone (206) (e.g., the input module (150) of FIG. 1), a speaker (205) (e.g., the audio output module (155) of FIG. 1), a display module (204) (e.g., the display module (160) of FIG. 1), a memory (207) (e.g., the memory (130) of FIG. 1), or a processor (203) (e.g., the processor (120) of FIG. 1). The above-listed components may be operatively or electrically connected to each other.

[0058] The communication interface (202) of one embodiment may be configured to connect to an external device and transmit and receive data. The microphone (206) of one embodiment may receive sound (e.g., user speech) and convert it into an electrical signal. The speaker (205) of one embodiment may output the electrical signal as sound (e.g., voice).

[0059] The display module (204) of one embodiment may be configured to display an image or a video. The display module (204) of one embodiment may also display a graphical user interface (GUI) of a running app (or application program). The display module (204) of one embodiment may receive touch input via a touch sensor. For example, the display module (204) may receive text input via a touch sensor in an on-screen keyboard area displayed within the display module (204).

[0060] In one embodiment, the memory (207) may store a client module (209), a software development kit (SDK) (208), and a plurality of apps. The client module (209) and the SDK (208) may constitute a framework (or solution program) for performing general functions. In addition, the client module (209) or the SDK (208) may constitute a framework for processing user input (e.g., voice input, text input, touch input).

[0061] The plurality of apps stored in the memory (207) of one embodiment may be programs for performing a specified function. According to one embodiment, the plurality of apps may include a first app (211_1) and a second app (211_2). According to one embodiment, each of the plurality of apps may include a plurality of operations for performing a specified function. For example, the apps may include an alarm app, a message app, and / or a schedule app. According to one embodiment, the plurality of apps may be executed by the processor (203) to sequentially execute at least some of the plurality of operations.

[0062] The processor (203) of one embodiment can control the overall operation of the electronic device (201). For example, the processor (203) can be electrically connected to a communication interface (202), a microphone (206), a speaker (205), and a display module (204) to perform a specified operation.

[0063] The processor (203) of one embodiment may also execute a program stored in the memory (207) to perform a designated function. For example, the processor (203) may execute at least one of the client module (209) or the SDK (208) to perform the following operations for processing user input. The processor (203) may control the operations of multiple apps, for example, through the SDK (208). The following operations described as operations of the client module (209) or the SDK (208) may be operations executed by the processor (203).

[0064] The client module (209) of one embodiment can receive user input. For example, the client module (209) can receive a voice signal corresponding to a user utterance detected through the microphone (206). Alternatively, the client module (209) can receive a touch input detected through the display module (204). Alternatively, the client module (209) can receive a text input detected through a keyboard or a visual keyboard. In addition, the client module (209) can receive various forms of user input detected through an input module included in the electronic device (201) or an input module connected to the electronic device (201). The client module (209) can transmit the received user input to the intelligent server (200). The client module (209) can transmit status information of the electronic device (201) to the intelligent server (200) together with the received user input. The status information can be, for example, execution status information of an app.

[0065] The client module (209) of one embodiment may receive a result corresponding to the received user input. For example, the client module (209) may receive a result corresponding to the received user input if the intelligent server (200) can produce a result corresponding to the received user input. The client module (209) may display the received result on the display module (204). Additionally, the client module (209) may output the received result as audio through the speaker (205).

[0066] In one embodiment, the client module (209) can receive a plan corresponding to the received user input. The client module (209) can display the results of executing multiple operations of the app according to the plan on the display module (204). For example, the client module (209) can sequentially display the results of executing multiple operations on the display module (204) and output audio through the speaker (205). The electronic device (201) can, for example, display only some results of executing multiple operations (e.g., the result of the last operation) on the display module (204) and output audio through the speaker (205).

[0067] According to one embodiment, the client module (209) may receive a request from the intelligent server (200) to obtain information necessary to produce a result corresponding to a user input. According to one embodiment, the client module (209) may transmit the necessary information to the intelligent server (200) in response to the request.

[0068] The client module (209) of one embodiment can transmit result information of executing multiple operations according to a plan to the intelligent server (200). The intelligent server (200) can use the result information to confirm that the received user input has been processed correctly.

[0069] The client module (209) of one embodiment may include a voice recognition module. According to one embodiment, the client module (209) may recognize voice inputs to perform limited functions through the voice recognition module. For example, the client module (209) may execute an intelligent app to process voice inputs to perform organic actions through designated inputs (e.g., "Wake up!").

[0070] An intelligent server (200) of one embodiment can receive information related to a user voice input from an electronic device (201) via a communication network. According to one embodiment, the intelligent server (200) can change data related to the received voice input into text data. According to one embodiment, the intelligent server (200) can generate a plan for performing a task corresponding to the user voice input based on the text data.

[0071] In one embodiment, the plan may be generated by an artificial intelligence (AI) system. The AI ​​system may be a rule-based system, a neural network-based system (e.g., a feedforward neural network (FNN) or a recurrent neural network (RNN)), or a combination of the above or another AI system. In one embodiment, the plan may be selected from a set of predefined plans or may be generated in real time in response to a user request. For example, the AI ​​system may select at least one plan from a plurality of predefined plans.

[0072] An intelligent server (200) of one embodiment may transmit a result according to a generated plan to an electronic device (201), or transmit the generated plan to the electronic device (201). According to one embodiment, the electronic device (201) may display a result according to the plan on a display module (204). According to one embodiment, the electronic device (201) may display a result of executing an operation according to the plan on a display module (204).

[0073] An intelligent server (200) of one embodiment may include a front end (215), a natural language platform (220), a capsule database (230), an execution engine (240), an end user interface (250), a management platform (260), a big data platform (270), or an analytic platform (280).

[0074] A front end (215) of one embodiment can receive a user input from an electronic device (201). The front end (215) can transmit a response corresponding to the user input.

[0075] According to one embodiment, the natural language platform (220) may include an automatic speech recognition module (ASR module) (221), a natural language understanding module (NLU module) (223), a planner module (225), a natural language generator module (NLG module) (227), or a text to speech module (TTS module) (229).

[0076] An automatic speech recognition module (221) of one embodiment may convert data related to a voice input received from an electronic device (201) into text data. A natural language understanding module (223) of one embodiment may determine a domain (and / or intent information) corresponding to a voice input (e.g., a user utterance) using text data of the voice input. A domain may correspond to a category (or service) associated with an action (or function) that a user wishes to perform using a device. A domain may be classified according to a service (e.g., an app) related to the text. For example, a Grace Note domain may correspond to a music search service (e.g., a Grace Note service). A Melon domain may correspond to a music playback service (e.g., a Melon service). A domain may be related to intent information corresponding to a text. A natural language understanding module (223) of one embodiment may identify a user's intent using text data of the voice input. For example, the natural language understanding module (223) can perform syntactic analysis or semantic analysis on user input in the form of text data to determine the user's intention. The natural language understanding module (223) of one embodiment can determine the meaning of words extracted from user input by using linguistic features (e.g., grammatical elements) of morphemes or phrases, and can match the meaning of the determined words to the intention to determine the user's intention. The natural language understanding module (223) can obtain intent information corresponding to the user's utterance. The intent information may be information indicating the user's intent determined by interpreting text data. The intent information may include information indicating an action (or function) that the user intends to execute using the device. A slot may be detailed information related to the intent information. The slot may be obtained based on a domain corresponding to the utterance.A slot may be variable information required to perform an action. In one embodiment, the variable information constituting a slot may include a named entity.

[0077] The planner module (225) of one embodiment can generate a plan using the intent and parameters determined by the natural language understanding module (223). According to one embodiment, the planner module (225) can determine a plurality of domains necessary to perform a task based on the determined intent. The planner module (225) can determine a plurality of operations included in each of the plurality of domains determined based on the intent. According to one embodiment, the planner module (225) can determine parameters necessary to execute the determined plurality of operations or result values ​​output by the execution of the plurality of operations. The parameters and the result values ​​can be defined as concepts of a specified format (or class). Accordingly, the plan can include a plurality of operations and a plurality of concepts determined by the user's intent. The planner module (225) can determine the relationship between the plurality of operations and the plurality of concepts in a stepwise (or hierarchical) manner. For example, the planner module (225) can determine the execution order of a plurality of actions based on the user's intention based on a plurality of concepts. In other words, the planner module (225) can determine the execution order of a plurality of actions based on parameters required for the execution of the plurality of actions and results output by the execution of the plurality of actions. Accordingly, the planner module (225) can generate a plan including association information (e.g., ontology) between the plurality of actions and the plurality of concepts. The planner module (225) can generate the plan using information stored in a capsule database (230) in which a set of relationships between concepts and actions is stored.

[0078] The natural language generation module (227) of one embodiment can convert specified information into text format. The information converted into text format may be in the form of natural language utterances. The text-to-speech conversion module (229) of one embodiment can convert information in text format into information in speech format.

[0079] According to one embodiment, some or all of the functions of the natural language platform (220) may also be implemented in the electronic device (201).

[0080] The capsule database (230) may store information on the relationships between a plurality of concepts and actions corresponding to a plurality of domains. According to one embodiment, a capsule may include a plurality of action objects (or action information) and concept objects (or concept information) included in a plan. According to one embodiment, the capsule database (230) may store a plurality of capsules in the form of a concept action network (CAN). According to one embodiment, the plurality of capsules may be stored in a function registry included in the capsule database (230).

[0081] The capsule database (230) may include a strategy registry that stores strategy information required when determining a plan corresponding to a voice input. The strategy information may include reference information for determining a single plan when there are multiple plans corresponding to a user input. According to one embodiment, the capsule database (230) may include a follow-up registry that stores information on follow-up actions for suggesting follow-up actions to a user in a given situation. The follow-up actions may include, for example, follow-up utterances. According to one embodiment, the capsule database (230) may include a layout registry that stores layout information of information output through the electronic device (201). According to one embodiment, the capsule database (230) may include a vocabulary registry that stores vocabulary information included in capsule information. According to one embodiment, the capsule database (230) may include a dialog registry that stores information on dialogue (or interaction) with a user. The capsule database (230) may update stored objects through a developer tool. The developer tool may include, for example, a function editor for updating action objects or concept objects. The developer tool may include a vocabulary editor for updating vocabulary. The developer tool may include a strategy editor for creating and registering strategies that determine plans. The developer tool may include a dialog editor for creating dialogues with the user.The developer tool may include a follow-up editor that activates follow-up goals and allows editing of follow-up utterances that provide hints. The follow-up goals may be determined based on the currently set goals, user preferences, or environmental conditions. In one embodiment, the capsule database (230) may also be implemented within the electronic device (201).

[0082] The execution engine (240) of one embodiment can produce a result using the generated plan. The end user interface (250) can transmit the produced result to the electronic device (201). Accordingly, the electronic device (201) can receive the result and provide the received result to the user. The management platform (260) of one embodiment can manage information used in the intelligent server (200). The big data platform (270) of one embodiment can collect user data. The analysis platform (280) of one embodiment can manage the quality of service (QoS) of the intelligent server (200). For example, the analysis platform (280) can manage the components and processing speed (or efficiency) of the intelligent server (200).

[0083] In one embodiment, a service server (300) may provide a service (e.g., food ordering or hotel reservation) specified to an electronic device (201). According to one embodiment, the service server (300) may be a server operated by a third party. Services of the service server (300), such as CP Service A (301) and CP Service B (302), may interact with the front end (215) of the intelligent server (200). The service server (300) in one embodiment may provide information to the intelligent server (200) for generating a plan corresponding to the received user input. The provided information may be stored in the capsule database (230). In addition, the service server (300) may provide result information according to the plan to the intelligent server (200).

[0084] In the integrated intelligence system (20) described above, the electronic device (201) can provide various intelligent services to the user in response to user input. The user input may include, for example, input via a physical button, touch input, or voice input.

[0085] In one embodiment, the electronic device (201) may provide a voice recognition service through an intelligent app (or voice recognition app) stored internally. In this case, for example, the electronic device (201) may recognize a user utterance or voice input received through the microphone and provide the user with a service corresponding to the recognized voice input.

[0086] In one embodiment, the electronic device (201) may perform a designated operation based on the received voice input, either alone or together with the intelligent server (200) and / or the service server (300). For example, the electronic device (201) may execute an app corresponding to the received voice input and perform a designated operation through the executed app.

[0087] In one embodiment, when an electronic device (201) provides a service together with an intelligent server (200) and / or a service server (300), the electronic device (201) may detect a user's speech using the microphone (206) and generate a signal (or voice data) corresponding to the detected user's speech. The electronic device (201) may transmit the voice data to the intelligent server (200) using the communication interface (202).

[0088] According to one embodiment, an intelligent server (200) may generate a plan for performing a task corresponding to a voice input received from an electronic device (201), or a result of performing an operation according to the plan, in response to a voice input. The plan may include, for example, a plurality of operations for performing a task corresponding to a user's voice input, and a plurality of concepts related to the plurality of operations. The concept may define parameters input to the execution of the plurality of operations, or result values ​​output by the execution of the plurality of operations. The plan may include association information between the plurality of operations and the plurality of concepts.

[0089] An electronic device (201) of one embodiment can receive the response using a communication interface (202). The electronic device (201) can output a voice signal generated within the electronic device (201) to the outside using the speaker (205), or can output an image generated within the electronic device (201) to the outside using the display module (204).

[0090]

[0091] FIG. 3 is a diagram showing a form in which relationship information between concepts and actions is stored in a database according to various embodiments.

[0092] The capsule database (e.g., the capsule database (230) of FIG. 2) of the intelligent server (e.g., the intelligent server (200) of FIG. 2) may store capsules in the form of a CAN (concept action network) (400). The capsule database may store operations for processing tasks corresponding to a user's voice input and parameters necessary for the operations in the form of a CAN (concept action network).

[0093] The capsule database may store a plurality of capsules (capsule (A) (401), capsule (B) (404)) corresponding to each of a plurality of domains. In one embodiment, one capsule (e.g., capsule (A) (401)) may correspond to one domain (e.g., location (geo), application). In addition, one capsule may correspond to at least one service provider (e.g., CP 1 (402) or CP 2 (403)) for performing a function for a domain related to the capsule. In one embodiment, one capsule may include at least one operation (410) and at least one concept (420) for performing a designated function. CAN (400) may store other information such as CP 3 (406). In addition, capsule B (404) may correspond to a service provider (e.g., CP 4 (405)).

[0094] The above natural language platform (e.g., the natural language platform (220) of FIG. 2) can generate a plan for performing a task corresponding to a received voice input using capsules stored in a capsule database. For example, the planner module of the natural language platform (e.g., the planner module (225) of FIG. 2) can generate a plan using capsules stored in a capsule database. For example, a plan (407) can be generated using actions (4011, 4013) and concepts (4012, 4014) of capsule A (401) and actions (4041) and concepts (4042) of capsule B (404).

[0095]

[0096] FIG. 4 is a diagram illustrating a screen in which an electronic device according to various embodiments processes voice input received through an intelligent app.

[0097] The electronic device (201) can execute an intelligent app to process user input through an intelligent server (e.g., the intelligent server (200) of FIG. 2).

[0098] According to one embodiment, on screen 310, when the electronic device (201) recognizes a designated voice input (e.g., wake up!) or receives an input via a hardware key (e.g., a dedicated hardware key), the electronic device (201) may execute an intelligent app for processing the voice input. For example, the electronic device (201) may execute an intelligent app while executing a schedule app. According to one embodiment, the electronic device (201) may display an object (e.g., an icon) (311) corresponding to the intelligent app on the display module (204) (e.g., the display module (160) of FIG. 1). According to one embodiment, the electronic device (201) may receive a voice input by a user's speech. For example, the electronic device (201) may receive a voice input such as "Tell me my schedule for this week!" According to one embodiment, the electronic device (201) can display a user interface (UI) (313) (e.g., an input window) of an intelligent app displaying text data of received voice input on a display module (204).

[0099] According to one embodiment, on the 320 screen, the electronic device (201) may display a result corresponding to the received voice input on the display module (204). For example, the electronic device (201) may receive a plan corresponding to the received user input and display 'this week's schedule' on the display module (204) according to the plan.

[0100]

[0101] FIG. 5 is a diagram illustrating an operation of an electronic device processing a user's speech according to one embodiment.

[0102] Referring to FIG. 5, according to one embodiment, the electronic device (501) may include at least a part of the configuration of the electronic device (101) described with reference to FIG. 1 and the electronic device (201) described with reference to FIG. 2. The intelligent server (601) may include at least a part of the configuration of the intelligent server (200) described with reference to FIG. 2. With respect to the electronic device (501) and the intelligent server (601), any description overlapping with that described with reference to FIGS. 1 to 4 will be omitted.

[0103] According to one embodiment, an electronic device (501) (e.g., the electronic device (101) of FIG. 1 or the electronic device (201) of FIG. 2) and an intelligent server (601) (e.g., the intelligent server (200) of FIG. 2) may be connected via a local area network (LAN), a wide area network (WAN), a value added network (VAN), a mobile radio communication network, a satellite communication network, or a combination thereof. The electronic device (501) and the intelligent server (601) may communicate with each other via a wired communication method or a wireless communication method (e.g., wireless LAN (WiFi), Bluetooth, Bluetooth low energy, ZigBee, WiFi direct (WFD), ultra wide band (UWB), infrared data association (IrDA), near field communication (NFC)).

[0104] According to one embodiment, the electronic device (501) may be implemented as at least one of a smartphone, a tablet personal computer, a mobile phone, a speaker (e.g., an AI speaker), a video phone, an e-book reader, a desktop personal computer, a laptop personal computer, a netbook computer, a workstation, a server, a personal digital assistant (PDA), a portable multimedia player (PMP), an MP3 player, a mobile medical device, a camera, or a wearable device.

[0105] According to one embodiment, the electronic device (501) may obtain a voice signal corresponding to a user's speech and transmit the voice signal to an intelligent server (601). The intelligent server (601) may obtain text data corresponding to the user's speech based on the voice signal. The text data may be converted into computer-readable text by performing automatic speech recognition (ASR) on the voice signal. The intelligent server (601) may analyze the user's speech using the text data. The intelligent server (601) may use the analysis results (e.g., intent information, entities, and / or capsules) to perform a necessary function or provide a response (e.g., a question, an answer) to the user to a device (e.g., the electronic device (501)). The intelligent server (601) may be implemented in software. Part or all of the intelligent server (601) may be implemented in the electronic device (501) and / or the intelligent server (601) (e.g., the intelligent server (200) of FIG. 2). An on-device artificial intelligence (AI) capable of processing speech without communication with an intelligent server (601) may be installed in an electronic device (501). Components such as the natural language platform (220) described with reference to FIGS. 2 to 4 may be implemented in the electronic device (501).

[0106] According to one embodiment, the automatic speech recognition module (221) included in the natural language platform (220) of FIG. 2 can convert a user utterance into text data. The natural language understanding module (223) included in the natural language platform (220) can determine a domain (and / or intent information) corresponding to the user utterance using the text data corresponding to the user utterance. The electronic device (501) can provide a response corresponding to the user utterance based on the intent information.

[0107] In one embodiment, the electronic device (501) can provide a response to the user that includes biased information. By providing a biased response, the electronic device (501) can interact with the user in an interactive manner on various issues. An electronic device (501) that provides a biased response can enhance the user experience in terms of diversity.

[0108] In one embodiment, the electronic device (501) may also provide information regarding the bias of the response when providing a response. By providing the user with information regarding the bias of the response (and / or the bias of the entire conversation), the user can recognize that the response of the electronic device (501) is biased. The electronic device (501) can ensure the objectivity of the response.

[0109] In one embodiment, biased information may be information influenced by personal opinions, prejudices, or the deliberate intent to promote a particular point of view. Biased information may include distorted content. Biased information may deviate from a fair and balanced representation of facts or perspectives. Informational bias may manifest in various forms, including political, ideological, cultural, or personal biases. According to embodiments of the present invention, bias is not limited to the dictionary definition of bias. Bias may include characteristics such as sensationalism, violence, and hate speech. In other words, the filtered information may correspond to unfiltered information. According to embodiments of the present invention, bias may be a term encompassing equivalent expressions. The degree of bias contained in a response may not deviate from conventional ethical concepts. For example, if a setting is favorable to a certain country, responses (e.g., "That country has better scenery than other countries, so it's a good place to live") may be provided to the user, but responses (e.g., "People from that country are a superior race worthy of conquering the world") (e.g., "Answer containing socially problematic bias") will not be provided to the user. Bias can involve the systematic distortion of statistical results due to factors not allowed in the derivation of statistical results. Bias can operate within a predetermined range. Bias can consist of a bias in favor or against one thing, person, or group compared to another.

[0110] Referring to FIG. 5, according to one embodiment, an electronic device (501) may receive an utterance from a user (e.g., "Do you think our country (Country A) will win in the match between Country A and Country B?"). The utterance (e.g., "Do you think our country (Country A) will win in the match between Country A and Country B?") may be an utterance that contains bias (e.g., Our country (Country A) = User's nationality). Based on the utterance, the electronic device (501) may generate a response that includes biased information (e.g., "Of course, I think our country (Country A) will win"). The electronic device (501) may provide the response that includes biased information (e.g., "Of course, I think our country (Country A) will win") to the user. When providing the response (e.g., "Of course, I think our country (Country A) will win"), the electronic device (501) may also provide the user with information about the bias of the response (e.g., see FIG. 8). The electronic device (501) can enhance the user experience in terms of diversity.

[0111] According to one embodiment, at least a portion of the operations performed by the electronic device (501) may be performed by the electronic device (501) and / or the intelligent server (601). The following description will be continued on the premise that the electronic device (501) performs the operations.

[0112]

[0113] FIG. 6 is a schematic block diagram of an electronic device according to one embodiment, and FIG. 7 is a drawing for explaining information about bias according to one embodiment.

[0114] Referring to FIG. 6, according to one embodiment, the electronic device (501) may include at least a part of the configuration of the electronic device (101) described with reference to FIG. 1 and the electronic device (201) described with reference to FIG. 2. As described above, an on-device artificial intelligence (AI) capable of processing speech without communication with an intelligent server (e.g., the intelligent server (200) of FIG. 2, the intelligent server (601) of FIG. 5) may be installed in the electronic device (501). That is, the natural language platform (220) described with reference to FIGS. 2 to 4 may be implemented in the electronic device (501). With respect to the electronic device (501), any description that overlaps with the description with reference to FIGS. 1 to 4 will be omitted.

[0115] According to one embodiment, the electronic device (501) may include a wireless communication module (540) (e.g., the wireless communication module (192) of FIG. 1). The electronic device (501) may include a processor (520) (e.g., the processor (120) of FIG. 1, the processor (203) of FIG. 2). The electronic device (501) may include a memory (530) (e.g., the memory (130) of FIG. 1, the memory (207) of FIG. 2). The processor (520) (e.g., an application processor) may access the memory (530) to execute instructions. The processor (520) may cause the electronic device (501) to provide a response to a user. The memory (530) may store various data used by at least one component (e.g., the processor (520)) of the electronic device (501). The memory (530) can store a general language model (531) and a biased language model (532).

[0116] In one embodiment, an electronic device (501) may receive a user's speech. The user may speak with a bias. The user may desire to receive a biased response in response to their speech, and the user may also perform user settings associated with the bias.

[0117] According to one embodiment, the electronic device (501) may obtain a result of a bias analysis of an utterance (e.g., first information on the bias of the utterance) based on the bias check module (521-1). The electronic device (501) may obtain a result of a bias analysis of a user (e.g., second information on the bias of the user) based on the bias check module (521-2). The first information on the bias of the utterance may include a bias category of the utterance and / or a degree of bias of the utterance. The second information on the bias of the user may correspond to a user setting associated with the bias. The second information on the bias of the user may be obtained based on a bias setting user interface (e.g., the bias setting user interface (921) of FIG. 9) displayed by the electronic device (501).

[0118] According to one embodiment, the bias check module (521-1) may be trained based on a corpus labeled with bias categories and degrees of bias. The bias check module (521-1) may analyze (e.g., determine) the bias of an utterance based on the corpus, which is training data. The corpus may serve as a criterion for determining the bias of an utterance. The bias check module (521-1) may analyze (e.g., determine) the bias of an utterance based on the correlation (e.g., similarity) between the corpus and the utterance. The bias check module (521-1) may generate a bias analysis result of the utterance (e.g., first information on the bias of the utterance).

[0119] According to one embodiment, referring to FIG. 7, an example of first information on the bias of an utterance can be confirmed. The information on bias (701) may correspond to an utterance (702). The bias categories may include demographic bias (e.g., racial bias, gender bias, age bias, national bias), toxicity (e.g., words, phrases, sentences that may be inappropriate or offensive), privacy (e.g., privacy issues), robustness, fairness (e.g., equal opportunities and equal treatment for diverse groups), sensitive topics, controversial content (e.g., controversial content), model vulnerability (e.g., offensive input to a voice assistant model), user experience, and others. As described above with reference to FIG. 5, according to embodiments of the present invention, bias is not limited to bias in the dictionary sense. That is, biased information may correspond to information that is not filtered. According to embodiments of the present invention, bias may be a term encompassing equivalent expressions.

[0120] In one embodiment, the utterance (702) may include demographic bias (e.g., national bias) and a sensitive topic (e.g., hooliganism). The bias information (701) may include the degree of bias for each bias category (e.g., demographic bias - 0.6, sensitive topic - 0.2).

[0121] According to one embodiment, the bias check module (521-2) may retrieve a user's setting value (e.g., the user's bias analysis result) (e.g., second information about the user's bias). The second information about the user's bias may correspond to a value set by the user before or after receiving the utterance. The user's setting associated with the bias may include a setting for a bias category (e.g., see FIG. 7) and / or a setting for a degree of bias (e.g., a value between 0 and 1). The user's setting associated with the bias may include a setting for a direction of the bias (e.g., left or right in the political category, or country A or country B in the country category). If the user sets the electronic device (501) to kid mode, the electronic device (501) may be configured not to provide a response that includes biased information. The second information about the user's bias may also include a user input obtained during the utterance (e.g., "Please allow a bias toward political aspects in the future conversation").

[0122] According to one embodiment, the electronic device (501) may generate a prompt based on a prompt generation module (522) from first information (e.g., first information about the bias of an utterance) and / or second information (e.g., second information about the bias of a user). The prompt may be intended to reduce the time required for retraining and fine-tuning a large-scale language model (e.g., a general language model (531) and / or a biased language model (532)).

[0123] According to one embodiment, the electronic device (501) may generate a response including biased information from a prompt based on a general language model (531) and / or a biased language model (532). The biased language model (532) may be trained based on a corpus in which bias categories and degrees of bias are labeled. The electronic device (501) may preprocess the corpus in advance to train the biased language model (532). The electronic device (501) may label the biased categories and degrees of bias in the corpus. The electronic device (501) may train the biased language model (532) based on the corpus in which the biased categories and degrees of bias are labeled. The corpus for training the biased language model (532) may be substantially similar to the corpus for training the bias check module (521-1). The biased language model (532) may generate a response including biased information. In Fig. 6, the general language model (531) and the biased language model (532) are expressed as separate models, but this is not limited to this. The general language model (531) and the biased language model (532) may also be implemented as a single model.

[0124] According to one embodiment, the electronic device (501) may generate information on the bias of a response (e.g., a response including biased information). The information on the bias of the response may be generated by the bias check module (521-3). The information on the bias of the response may be configured in a format similar to the format of the first information on the bias of the utterance (e.g., see FIG. 7 ). The information on the bias of the response may be visually displayed (e.g., see the information on the bias of the response (512) of FIG. 8 ). The bias check module (521-3) that generates the information on the bias of the response may be trained based on a corpus labeled with bias categories and degrees of bias. The corpus for training the bias check module (521-3) may be substantially similar to the corpus for training the bias check module (521-1) and / or the corpus for training the biased language model (532).

[0125] In one embodiment, the bias check module (521-1, 521-3) can distinguish various types of bias, as well as abusive language and illegal content. A typical bias check module may perform operations to remove bias from responses generated by a language model (e.g., removing biased corpora). The bias check module (521-1, 521-3) may collect a biased corpus (e.g., a corpus labeled with bias categories and degrees of bias) and utilize the biased corpus.

[0126] In one embodiment, the electronic device (501) may provide the user with information about a response containing biased information and the bias of the response. Depending on the user's settings (e.g., the results of a bias analysis of the user's utterance) or the results of a bias analysis of the utterance, the degree of bias of the information included in the response or the bias of the information included in the response may vary.

[0127] In one embodiment, if a user desires a biased conversation on a specific topic, the electronic device (501) can organize opposing and supporting opinions or N subtopics on the topic. This process may utilize argumentative essay evaluation technology. The electronic device (501) may evaluate the clarity of arguments and evidence. For example, if two positions on a topic are identified, the electronic device (501) may reference and briefly explain the most cited or viewed representative documents for each position. The user may select a position and proceed with the conversation. Depending on the position selected by the user, the electronic device (501) may generate a response to the argument and evidence based on the collected documents. The electronic device (501) may provide links to access the references used as the basis for the conversation through the UI, and may also organize and display the conversation content in a summarized form.

[0128]

[0129] FIGS. 8 to 12 are diagrams illustrating an operation of an electronic device processing a user's speech according to one embodiment.

[0130] Referring to FIG. 8, in a situation (801), an electronic device (800) may receive an utterance from a user (e.g., “Do you think our country (Country A) will win in the match between Country A and Country B?”). The utterance (e.g., “Do you think our country (Country A) will win in the match between Country A and Country B?”) may be an utterance that contains bias (e.g., Our country (Country A) = User’s nationality). An electronic device (800) designed to remove bias can only provide a typical response (e.g., “Both countries are interested in the match between Country A and Country B. I don’t know who will win.”) to the user in response to an utterance that contains bias.

[0131] In one embodiment, in a situation (802), the electronic device (501) may receive an utterance from a user (e.g., "Do you think our country (Country A) will win in the match between Country A and Country B?"). The utterance (e.g., "Do you think our country (Country A) will win in the match between Country A and Country B?") may be an utterance that contains bias (e.g., Our country (Country A) = User's nationality). Based on the utterance, the electronic device (501) may generate a response that includes biased information (e.g., "Of course, I think our country (Country A) will win"). The electronic device (501) may provide the response (511) that includes biased information to the user (e.g., "Of course, I think our country (Country A) will win"). When providing the response (511), the electronic device (501) may also provide the user with information (512) about the bias of the response. Information (512) about the bias of the response can be visually displayed through the screen (510). The electronic device (501) can enhance the user experience in terms of diversity.

[0132] Referring to FIG. 9, according to one embodiment, an electronic device (501) may receive an utterance from a user (e.g., "Who do you think will win in a match between country A and country B?"). Prior to receiving the utterance, the user may pre-set settings related to bias. The user's settings related to bias may include settings for a bias category (e.g., see FIG. 7) and / or a setting for a degree of bias (e.g., a value between 0 and 1). The user's settings related to bias may include settings for a direction of bias (e.g., left or right in a political category, or country A or country B in a country category). The user's settings related to bias may also be performed after the utterance. For example, the electronic device (501) may, in response to receiving an utterance (e.g., “Who do you think will win in a match between countries A and B?”), provide a user interface (e.g., a bias setting user interface (921)) via the screen (510) that allows the user to select a direction of bias (e.g., whether country A or country B in a country category). The electronic device (501) may receive a user’s touch input via the screen (510) (e.g., a display). The subsequent response of the electronic device (501) may vary depending on the user’s touch input.

[0133] In one embodiment, in a situation (901), the electronic device (501) may receive a touch input from a user who selects country A for a bias setting user interface (921). The electronic device (501) may generate a response (910) that includes information biased toward country A (e.g., "Country A is ahead in recent records. I think Country A will win"). The electronic device (501) may provide the response (910) that includes information biased toward country A to the user (e.g., "Country A is ahead in recent records. I think Country A will win"). When providing the response (910), the electronic device (501) may also provide the user with information (911) about the bias of the response (910) (e.g., the flag of country A). The information (911) about the bias of the response (910) may be visually displayed through the screen (510).

[0134] According to one embodiment, in a situation (902), the electronic device (501) may receive a touch input from a user who selects country B for a bias setting user interface (921). The electronic device (501) may generate a response (913) including information biased toward country B (e.g., “Country B is the strongest soccer country in Asia. I think country B will win”). The electronic device (501) may provide the response (913) including information biased toward country B to the user. When providing the response (913), the electronic device (501) may also provide the user with information (914) about the bias of the response (913) (e.g., the flag of country B). The information (914) about the bias of the response (913) may be visually displayed through the screen (510). By also providing the user with information (911, 914) about the bias of the response (910, 913), the user can recognize that the response of the electronic device (501) is biased. The electronic device (501) can ensure objectivity in the response.

[0135] Referring to FIG. 10, according to one embodiment, an electronic device (501) may receive an utterance (e.g., "In the match between Country A and Country B, our country (Country A) will win. Tell me from the perspectives of both teams") from a user. The utterance (e.g., "In the match between Country A and Country B, our country (Country A) will win. Tell me from the perspectives of both teams") may be an utterance that desires responses from various perspectives. Based on the utterance, the electronic device (501) may generate a plurality of responses (1001, 1002, 1003) each having a different bias. The responses (1001, 1003) may be responses biased toward Country A. The response (1002) may be a response biased toward Country B. The plurality of responses (1001, 1002, 1003) may be configured in a form of continuing a conversation between each other. Multiple responses (1001, 1002, 1003) can be provided to the user via the screen (510).

[0136] Referring to FIG. 11, according to one embodiment, an electronic device (501) may receive an utterance (e.g., "I think Country A is the best country in the world") from a user. The utterance (e.g., "I think Country A is the best country in the world") may be an utterance containing bias. Based on the utterance, the electronic device (501) may generate a plurality of responses (1101, 1102, 1103) each having a different bias. The plurality of responses (1101, 1102, 1103) may be provided to the user through a screen (510). The plurality of responses (1101, 1102, 1103) may be composed of three or more responses. The electronic device (501) may enhance the user experience in terms of diversity.

[0137] Referring to FIG. 12, according to one embodiment, the electronic device (501) may provide a user with responses that are biased to different degrees based on the results of the bias analysis of the utterance. In a situation (1201), the electronic device (501) may receive a relatively less biased (e.g., compared to the situation (1202)) utterance (“Isn’t our country (Country A) one of the best soccer players in East Asia?”). In a situation (1201), the electronic device (501) may provide a relatively less biased (e.g., compared to the situation (1202)) response (“I think our country (Country A) is one of the best soccer players in East Asia”) to the user. In a situation (1202), the electronic device (501) may receive a relatively more biased (e.g., compared to the situation (1201)) utterance (“Isn’t our country (Country A) one of the best soccer players in East Asia?”). In situation (1202), the electronic device (501) can provide a relatively more biased (e.g., compared to situation (1201)) response to the user (e.g., “Of course, in East Asia, our country (Country A) is the best at soccer!”).

[0138]

[0139] FIG. 13 illustrates a flowchart of a method of operating an electronic device according to one embodiment.

[0140] Actions 1310 to 1340 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each action (1310 to 1340) may be changed, and at least two actions may be performed in parallel.

[0141] According to one embodiment, operations 1310 to 1340 may be understood to be performed in a processor (e.g., processor (520) of FIG. 6) of an electronic device (e.g., electronic device (501) of FIG. 6).

[0142] In operation 1310, an electronic device according to one embodiment (e.g., electronic device (501) of FIG. 5 ) may receive a user's speech.

[0143] In operation 1320, an electronic device (501) according to one embodiment may generate a response including biased information based on the utterance.

[0144] In operation 1330, the electronic device (501) according to one embodiment may generate information about bias of the response based on the response.

[0145] In operation 1340, an electronic device (501) according to one embodiment may provide the user with information about the bias and a response.

[0146]

[0147] An electronic device according to one embodiment (e.g., electronic device (101) of FIG. 1, electronic device (201) of FIG. 2, electronic device (501) of FIG. 5) may include a memory (e.g., memory (130) of FIG. 1, memory (207) of FIG. 2, memory (530) of FIG. 6) storing one or more computer programs. The electronic device may include a processor (e.g., processor (120) of FIG. 1, processor (203) of FIG. 2, processor (520) of FIG. 6) communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to analyze a bias of the speech or a bias of the user. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response including biased information based on the bias analysis results of the utterance or the user. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the response to the user.

[0148] In one embodiment, to analyze the bias of the user, the one or more computer programs may further include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to determine a plurality of bias directions based on the utterance. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the user with a bias-setting user interface including the plurality of bias directions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a bias setting based on a bias direction selected from among the plurality of bias directions.

[0149] In one embodiment, to provide the response to the user, the one or more computer programs may further include computer-executable instructions. The computer-executable instructions, when executed by the one or more processors, may cause the electronic device to visually display the bias setting along with the response.

[0150] According to one embodiment, the bias analysis result of the utterance may include at least one of a bias category of the utterance or a degree of bias of the utterance.

[0151] In one embodiment, the user bias analysis results may correspond to the user's bias-related settings. These settings may be obtained based on a bias setting user interface displayed by the electronic device.

[0152] In one embodiment, the one or more computer programs may further include computer-executable instructions. The computer-executable instructions, executed by the one or more processors, may cause the electronic device to generate information about the bias of the response based on the response. The computer-executable instructions, executed by the one or more processors, may cause the electronic device to visually display the information about the bias of the response.

[0153] According to one embodiment, the response may have a different degree of bias in the information to be included in the response or may have a different degree of bias in the information to be included in the response depending on the result of the bias analysis of the user or the result of the bias analysis of the utterance.

[0154] An electronic device according to one embodiment (e.g., electronic device (101) of FIG. 1, electronic device (201) of FIG. 2, electronic device (501) of FIG. 5) may include a memory (e.g., memory (130) of FIG. 1, memory (207) of FIG. 2, memory (530) of FIG. 6) storing one or more computer programs. The electronic device may include a processor (e.g., processor (120) of FIG. 1, processor (203) of FIG. 2, processor (520) of FIG. 6) communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response that includes biased information based on the speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate information about the bias of the response based on the response. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the user with the information about the bias and the response together.

[0155] According to one embodiment, the information about the bias may include at least one of a bias category of the response or a degree of bias of the response.

[0156] According to one embodiment, the response may be generated based on a general language model (e.g., general language model (531) of FIG. 6) and a biased language model (e.g., biased language model (532) of FIG. 6).

[0157] In one embodiment, the biased language model may be trained based on a corpus labeled with bias categories and degrees of bias.

[0158] In one embodiment, the response may have a different degree of bias in the information to be included in the response or may have a different degree of bias in the information to be included in the response depending on the user's settings or the results of the bias analysis of the utterance.

[0159] In one embodiment, the user's settings may be obtained based on a bias setting user interface displayed by the electronic device.

[0160] In one embodiment, the response may include multiple responses, each having a different bias.

[0161] In one embodiment, the information about the bias may be displayed visually.

[0162] In one embodiment, the one or more computer programs may further include computer-executable instructions, which, when executed by the one or more processors, may cause the electronic device to provide information about the bias of the entire conversation, including the utterance and the response.

[0163] An electronic device according to one embodiment (e.g., electronic device (101) of FIG. 1, electronic device (201) of FIG. 2, electronic device (501) of FIG. 5) may include a memory (e.g., memory (130) of FIG. 1, memory (207) of FIG. 2, memory (530) of FIG. 6) storing one or more computer programs. The electronic device may include a processor (e.g., processor (120) of FIG. 1, processor (203) of FIG. 2, processor (520) of FIG. 6) communicatively coupled to the memory. The one or more computer programs may include computer-executable instructions. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to receive a user's speech. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to obtain first information about a bias of the speech or second information about a bias of the user. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a prompt based on the first information or the second information. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to generate a response from the prompt, the response including biased information based on a general language model or a biased language model. The computer-executable instructions may be executed by the one or more processors to cause the electronic device to provide the response to the user.

[0164] According to one embodiment, the first information may include at least one of a bias category of the utterance or a degree of bias of the utterance.

[0165] In one embodiment, the second information may correspond to a setting of the user associated with bias.

[0166] In one embodiment, the biased language model may be trained based on a corpus labeled with bias categories and degrees of bias.

[0167] In one embodiment, the one or more computer programs may further include computer-executable instructions. The computer-executable instructions, executed by the one or more processors, may cause the electronic device to generate information about the bias of the response based on the response. The computer-executable instructions, executed by the one or more processors, may cause the electronic device to provide the user with information about the bias and the response together.

[0168] In one embodiment, the response may have a different degree of bias in the information to be included in the response or may have a different degree of bias in the information to be included in the response depending on the user's settings or the results of the bias analysis of the utterance.

[0169] According to one embodiment, one or more non-transitory computer-readable storage media are provided that store one or more computer programs including computer-executable instructions that are executed by one or more processors (e.g., processor 120 of FIG. 1, processor 203 of FIG. 2, processor 520 of FIG. 6) of an electronic device (e.g., electronic device 101 of FIG. 1, electronic device 201 of FIG. 2, electronic device 501 of FIG. 5) to cause the electronic device to perform operations. The operations may include receiving a user's utterance. The operations may include analyzing a bias of the utterance or a bias of the user. The operations may include generating a response including biased information based on a result of the analysis of the bias of the utterance or a result of the analysis of the bias of the user.

[0170]

[0171] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0172] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" may include any one of the items listed together with the corresponding phrase among the phrases, or all possible combinations thereof. Terms such as "first", "second", or "first" or "second" may be used simply to distinguish the corresponding component from other corresponding components and do not limit the corresponding components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as being "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0173] The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0174] Various embodiments of the present document may be implemented as software (e.g., a program (140)) including one or more instructions stored in a storage medium (e.g., an internal memory (136) or an external memory (138)) readable by a machine (e.g., an electronic device (101)). For example, a processor (e.g., a processor (120)) of the machine (e.g., an electronic device (101)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0175] According to one embodiment, the method according to various embodiments disclosed in this document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0176] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0177] While the present disclosure has been illustrated and described with reference to various embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents.

Claims

1. In an electronic device (101; 201; 501), A memory (130; 207; 530) storing one or more computer programs; and One or more processors (120; 203; 520) communicatively coupled to the above memory (130; 207; 530) Including, The one or more computer programs comprise computer-executable instructions, which are executed by the one or more processors (120; 203; 520) to cause the electronic device (101; 201; 501) to: Receive user speech, Analyze the bias of the above utterance or the bias of the above user, Based on the bias analysis result of the above utterance or the bias analysis result of the user, a response including biased information is generated, To provide the above response to the above user, Electronic devices (101; 201; 501).

2. In paragraph 1, The results of the bias analysis of the above utterance are as follows: comprising at least one of the bias category of the utterance or the degree of bias of the utterance; Electronic devices (101; 201; 501).

3. In either of paragraphs 1 and 2, The results of the above user bias analysis are as follows: Corresponds to the above user's settings related to bias, The above settings are, Obtained based on the bias setting user interface displayed by the above electronic device (101; 201; 501). Electronic devices (101; 201; 501).

4. In any one of paragraphs 1 to 3, To analyze the bias of the user, the one or more computer programs further include computer executable instructions, which are executed by the one or more processors (120; 203; 520) to cause the electronic device (101; 201; 501) to: Based on the above utterances, multiple directions of bias are determined, Providing the user with a bias-setting user interface that includes the directions of the plurality of biases, An electronic device (101; 201; 501) configured to receive a bias setting based on a bias direction selected from among the plurality of bias directions.

5. In any one of paragraphs 1 to 4, To provide said response to said user, said one or more computer programs further comprise computer executable instructions, which are executed by said one or more processors (120; 203; 520) to cause said electronic device (101; 201; 501) to: An electronic device (101; 201; 501) for visually displaying the bias setting together with the above response.

6. In any one of paragraphs 1 to 5, The one or more computer programs further comprise computer executable instructions, which are executed by the one or more processors (120; 203; 520) to cause the electronic device (101; 201; 501) to: Based on the above response, information about the bias of the response is generated, To visually display information about the bias of the above response, Electronic devices (101; 201; 501).

7. In any one of paragraphs 1 to 6, The above response is, Depending on the results of the bias analysis of the user or the bias analysis of the utterance, the degree of bias of the information to be included in the response may vary, or the bias of the information to be included in the response may vary. Electronic devices (101; 201; 501).

8. In electronic devices (101; 201; 501), A memory (130; 207; 530) storing one or more computer programs; and One or more processors (120; 203; 520) communicatively coupled to the above memory (130; 207; 530) Including, The one or more computer programs comprise computer-executable instructions, which are executed by the one or more processors (120; 203; 520) to cause the electronic device (101; 201; 501) to: Receive user speech, Based on the above utterance, a response containing biased information is generated, Based on the above response, information about bias of the response is generated, Providing the user with information about the bias and the response to it, Electronic devices (101; 201; 501).

9. In paragraph 8, Information about the above bias is: An electronic device (101; 201; 501) comprising at least one of a bias category of the response or a degree of bias of the response.

10. In either of paragraphs 8 and 9, The above response is, It is generated based on general language models and biased language models. Electronic devices (101; 201; 501).

11. In any one of paragraphs 8 to 10, The above biased language model, It is learned based on a corpus, labeled with bias categories and degrees of bias. Electronic devices (101; 201; 501).

12. In any one of paragraphs 8 to 11, The above response is, Depending on the user's settings or the results of the bias analysis of the utterance, the degree of bias of the information to be included in the response may vary, or the bias of the information to be included in the response may vary. Electronic devices (101; 201; 501).

13. In any one of paragraphs 8 to 12, The above user's settings are: Obtained based on the bias setting user interface displayed by the above electronic device (101; 201; 501). Electronic devices (101; 201; 501).

14. In any one of paragraphs 8 to 13, The above response is, Contains multiple responses with different biases, Electronic devices (101; 201; 501).

15. In any one of paragraphs 8 to 14, Information about the above bias is: What is displayed visually, Electronic devices (101; 201; 501).

Images