Method, apparatus, device and medium for intelligent voice device

Abstract

The present disclosure provides a method, apparatus, device and medium for intelligent voice equipment, which relates to the field of computer technology, and in particular to artificial intelligence and voice technology. The implementation scheme is: based on the user's biological characteristics, determine the user's age range; based on the age range, select a preset first speech rate parameter for broadcasting voice; in response to identifying the user's identity, adjust the first speech rate parameter based on the user's historical speech rate record to determine the second speech rate parameter, wherein the historical speech rate record includes the user-specific speech rate parameter extracted from the user's voiceprint feature in at least one interaction between the intelligent voice equipment and the user; and broadcast the voice based on the second speech rate parameter.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, in particular to artificial intelligence and voice technology, and specifically to a method, apparatus, electronic device, computer-readable storage medium, and computer program product for an intelligent voice device. Background Art

[0002] Artificial intelligence is a discipline that studies how to use computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.). It includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0003] Speech synthesis, also known as Text to Speech (TTS) technology, is a technology that converts text information generated by a computer or input from the outside into understandable and fluent Chinese spoken output.

[0004] The methods described in this section are not necessarily methods that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any method described in this section is considered to be prior art simply because it is included in this section. Similarly, unless otherwise indicated, the issues mentioned in this section should not be considered to have been recognized in any prior art. Summary of the invention

[0005] The present disclosure provides a method, an apparatus, an electronic device, a computer-readable storage medium, and a computer program product for an intelligent voice device.

[0006] According to one aspect of the present disclosure, a method for an intelligent voice device is provided, including: determining an age range of a user based on biometric features of the user; selecting a preset first speech rate parameter for broadcasting voice based on the age range; in response to identifying the identity of the user, adjusting the first speech rate parameter based on a historical speech rate record of the user to determine a second speech rate parameter, wherein the historical speech rate record includes a speech rate parameter specific to the user extracted from a voiceprint feature of the user during at least one interaction between the intelligent voice device and the user; and broadcasting voice based on the second speech rate parameter.

[0007] According to another aspect of the present disclosure, there is provided an apparatus for an intelligent voice device, comprising: a first determination unit, configured to determine an age range of a user based on a biometric feature of the user; a selection unit, configured to select a preset first speech rate parameter for broadcasting a voice based on the age range; a first adjustment unit, configured to adjust the first speech rate parameter based on a historical speech rate record of the user in response to identifying the identity of the user, wherein the historical speech rate record comprises a speech rate parameter specific to the user extracted from a voiceprint feature of the user in at least one interaction between the intelligent voice device and the user, so as to determine a second speech rate parameter; and a broadcasting unit, configured to broadcast the voice based on the second speech rate parameter.

[0008] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned method for an intelligent voice device.

[0009] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the above method for an intelligent voice device.

[0010] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program implements the above method for an intelligent voice device when executed by a processor.

[0011] According to another aspect of the present disclosure, an intelligent voice device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method executed by the above-mentioned intelligent voice device.

[0012] According to one or more embodiments of the present disclosure, the playback speed can be adjusted according to different age groups of users, and personalized adjustment of the playback speed for different users of the same age group can also be achieved.

[0013] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings exemplarily illustrate the embodiments and constitute a part of the specification, and together with the text description of the specification, are used to explain the exemplary implementation of the embodiments. The embodiments shown are for illustrative purposes only and do not limit the scope of the claims. In all drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0015] Figure 1 A schematic diagram showing an exemplary system in which the various methods described herein may be implemented according to an embodiment of the present disclosure;

[0016] Figure 2 A flow chart of a method for an intelligent voice device according to an embodiment of the present disclosure is shown;

[0017] Figure 3 A flow chart of determining the age range of a user according to an embodiment of the present disclosure is shown;

[0018] Figure 4 A flowchart of adjusting a first speech rate parameter based on a user's historical speech rate record according to an embodiment of the present disclosure is shown;

[0019] Figure 5 A flow chart of a method for an intelligent voice device according to an embodiment of the present disclosure is shown;

[0020] Figure 6 A flow chart of determining a second speech rate parameter based on a third speech rate parameter according to an embodiment of the present disclosure is shown;

[0021] Figure 7 A flow chart of a method for an intelligent voice device according to an embodiment of the present disclosure is shown;

[0022] Figure 8 A structural block diagram of an apparatus for an intelligent voice device according to an embodiment of the present disclosure is shown;

[0023] Fig. 9 shows a structural block diagram of a first determining unit according to an embodiment of the present disclosure;

[0024] Fig.10 A structural block diagram of an apparatus for an intelligent voice device according to an embodiment of the present disclosure is shown;

[0025] Fig.11 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0026] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0027] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0028] The terms used in the description of various examples in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. In addition, the term "and / or" used in this disclosure covers any one of the listed items and all possible combinations.

[0029] Existing intelligent voice devices only implement the function of adjusting the speech speed according to the user's age group, but cannot implement further personalized speech speed adjustment for different users of the same age group.

[0030] To solve the above problems, the present invention identifies the age group of the user and adjusts the playback speed according to the different age groups of the user; at the same time, the user's voiceprint features are extracted, and the playback speed of different users in the same age group is personalized adjusted through the user's historical speech speed records.

[0031] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0032] Figure 1 FIG. 1 is a schematic diagram of an exemplary system 100 in which various methods and apparatuses described herein may be implemented according to an embodiment of the present disclosure. Figure 1 , the system 100 includes one or more client devices 101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

[0033] In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable execution of the method for an intelligent voice device.

[0034] In some embodiments, server 120 may also provide other services or software applications that may include non-virtualized environments and virtualized environments. In some embodiments, these services may be provided as web-based services or cloud services, such as provided to users of client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0035] exist Figure 1 In the configuration shown, the server 120 may include one or more components that implement the functions performed by the server 120. These components may include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 may in turn utilize one or more client applications to interact with the server 120 to utilize the services provided by these components. It should be understood that a variety of different system configurations are possible, which may differ from the system 100. Therefore, Figure 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

[0036] The user may use client devices 101, 102, 103, 104, 105 and / or 106 to perform intelligent voice interaction with the client device. The client device may provide an interface that enables the user of the client device to interact with the client device. The client device may also output information to the user via the interface. Figure 1 Only six client devices are depicted, but one skilled in the art will appreciate that the present disclosure may support any number of client devices.

[0037] Client devices 101, 102, 103, 104, 105 and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, game systems, thin clients, various messaging devices, sensors or other sensing devices, etc. These computer devices may run various types and versions of software applications and operating systems, such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as GOOGLE Chrome OS); or include various mobile operating systems, such as MICROSOFT Windows Mobile OS, iOS, Windows Phone, Android. Portable handheld devices may include cellular phones, smart phones, tablet computers, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Game systems may include various handheld game devices, Internet-enabled game devices, etc. Client devices are capable of executing various different applications, such as various Internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and may use various communication protocols.

[0038] The network 110 may be any type of network known to those skilled in the art that may support data communications using any of a variety of available protocols, including but not limited to TCP / IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a local area network (LAN), an Ethernet-based network, a token ring, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0039] Server 120 may include one or more general purpose computers, dedicated server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running virtual operating systems, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain a server's virtual storage device). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0040] The computing units in the server 120 may run one or more operating systems including any of the above operating systems and any commercially available server operating systems. The server 120 may also run any of a variety of additional server applications and / or middle-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0041] In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0042] In some embodiments, the server 120 may be a server of a distributed system, or a server combined with a blockchain. The server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in a cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

[0043] The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as audio files and video files. The data repository 130 may reside in various locations. For example, the data repository used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The data repository 130 may be of different types. In some embodiments, the data repository used by the server 120 may be a database, such as a relational database. One or more of these databases may store, update, and retrieve data to and from the database in response to a command.

[0044] In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the applications may be different types of databases, such as a key-value store, an object store, or a conventional store backed by a file system.

[0045] Figure 1The system 100 may be configured and operated in various ways to enable the application of various methods and apparatuses described in the present disclosure.

[0046] According to one aspect of the present disclosure, a method for an intelligent voice device is provided. Figure 2 As shown, the method includes: step 201, determining the age range of the user based on the user's biometric characteristics; step 202, selecting a preset first speech rate parameter for broadcasting voice based on the age range; step 203, in response to identifying the identity of the user, adjusting the first speech rate parameter based on the user's historical speech rate record to determine the second speech rate parameter, wherein the historical speech rate record includes a user-specific speech rate parameter extracted from the user's voiceprint features in at least one interaction between the intelligent voice device and the user; and step 204, broadcasting voice based on the second speech rate parameter.

[0047] Therefore, by identifying the user's age group, the playback speed can be adjusted according to the user's different age groups; at the same time, the user's voiceprint features are extracted, and the playback speed of different users in the same age group can be personalized adjusted through the user's historical speech speed records.

[0048] The speech rate parameter is a parameter in speech synthesis. In the speech synthesis process, the speech rate of the synthesized speech is adjusted by adjusting the size of the parameter. The speech rate parameter can be expressed as the number of words played per unit time or the time period required to play a unit number of words. It is understandable that those skilled in the art can set the expression form of the speech rate parameter by themselves, and this is not limited here.

[0049] The identification of the user's identity can be achieved by identifying one or more biometric features of face, voiceprint, fingerprint, and iris. When the user uses the intelligent voice device for the first time, the device will guide the user to enter the above features. For example, the device records the user's face image and iris image through the camera, records the user's voice audio by guiding the user to read a text, and records the user's fingerprint by guiding the user to touch the fingerprint recognition area. The device extracts and saves the features of the recorded face image, iris image, voice audio, and fingerprint. When identifying the user, the user's identity is determined by identifying one or more of the above biometric features and comparing them with the saved biometric features.

[0050] After the intelligent voice device recognizes the user's identity, during the voice interaction with the user, the device will extract the speech rate characteristics of the user's voiceprint features, and store the user's speech rate characteristics as a speech rate parameter value in the device. The speech rate parameter value is expressed as the number of words spoken by the user per unit time or the time period required for the user to speak a unit number of words. It is understandable that those skilled in the art can set the method of extracting the user's speech rate characteristics and the method of expressing the speech rate parameter value by themselves, which is not limited here.

[0051] According to some embodiments, the biometric features used to determine the age range of the user include the user's facial features and voiceprint features. Optionally, the recognition of the user's facial features mainly includes extracting skin texture, skin color, brightness and wrinkle texture, etc., and predicting the above facial features through a neural network model to obtain a predicted value of the user's age. Optionally, the recognition of the user's voiceprint features mainly includes voiceprint spectrum, rhythmic features, etc., and predicting the above voiceprint features through a neural network model to obtain a predicted value of the user's age. It is understandable that those skilled in the art can choose the extracted facial features and voiceprint features and the applied neural network prediction model at their own discretion, and no limitation is made here.

[0052] According to some embodiments, Figure 3 As shown, determining the age range of a user based on the user's biometric features includes: step 301, determining a first predicted age of the user based on the user's facial features; step 302, determining a second predicted age of the user based on the user's voiceprint features; step 303, in response to a difference between the first predicted age and the second predicted age not exceeding a first threshold, determining the age of the user to be the first predicted age; step 304, in response to a difference between the first predicted age and the second predicted age exceeding the first threshold, determining the age of the user to be the second predicted age; and step 305, determining the age range of the user based on the determined age of the user.

[0053] When the user's age is identified by facial features or voiceprint features alone, there may be a large error. Therefore, after predicting the user's age by the above two features respectively, the difference between the two predicted values ​​is compared. If the difference exceeds the first threshold, the predicted value of the voiceprint feature is used as the final predicted value of the user's age; otherwise, the predicted value of the facial feature is used as the final predicted value of the user's age. It is understandable that those skilled in the art can determine the first threshold by themselves through experiments, and it is not limited here.

[0054] After determining the final predicted value of the user's age, the age range corresponding to the user can be determined. The age range is preset in the intelligent voice device, and each preset age range corresponds to a preset speech speed parameter.

[0055] Optionally, when determining the age range corresponding to the user through the final predicted value of the user's age, first determine whether the user's age is within the confidence interval of the age range. If it is determined that it is within the confidence interval of the age range, then determine that the age range is the age range corresponding to the user; if it is determined that it is outside the confidence interval of the age range, then trigger the inquiry function of the device, inquire the user's age through voice or screen display whether it is within the age range, and determine the age range corresponding to the user based on the user's feedback. For example, when the user's age is identified as 21 years old, it is determined that the user's age is outside the confidence interval of the preset age range of 21-30 years old, that is, considering that there is a certain error in the identified user's age, there is a certain probability that the user's real age corresponds to the preset age range of 11-20 years old, so the user is asked to further improve the accuracy.

[0056] Therefore, by predicting the user's age based on the user's facial and voiceprint features respectively, and determining the user's final age prediction value by comparing the two prediction values, the accuracy of the user's age prediction can be further improved, so that the user's age range can be determined more accurately, and the device playback speed suitable for the user's age group can be selected.

[0057] According to some embodiments, Figure 4 As shown, in response to identifying the identity of the user, adjusting the first speech rate parameter based on the user's historical speech rate record includes: step S401, in response to identifying the identity of the user, reading at least one historical speech rate record of the user; step S402, performing normal distribution fitting on at least one historical speech rate record to calculate the normal distribution mean of at least one historical speech rate record; step S403, adjusting the first speech rate parameter based on the normal distribution mean.

[0058] The user's identity is determined by identifying one or more biometric features of the user's face, voiceprint, fingerprint, and iris, and at least one historical speech rate record of the user stored in the device is read. Considering that in daily life, when the user interacts with the device by voice, there may be situations where the speech rate deviates from the user's daily speech rate, such as being too fast or too slow. Therefore, a normal distribution fitting is performed on the at least one historical speech rate record of the user read, and the historical speech rate records with a confidence level lower than the preset confidence level are screened out through a preset confidence level, and the mean of the normal distribution is calculated.

[0059] Optionally, those skilled in the art may also filter out the speech speed records that deviate from the user's daily speech speed in other similar ways, such as by calculating the variance or standard deviation and filtering out the historical speech speed records with large variance or standard deviation, etc., which is not limited here.

[0060] Therefore, the records that deviate from the user's daily speech speed can be screened out through normal distribution fitting and other methods. The obtained average of the user's historical speech speed records can more accurately reflect the user's daily speech speed. Applying this average to adjust the device speech speed parameters can make the adjusted device speech speed more in line with the user's daily conversation habits.

[0061] According to some embodiments, Figure 5 As shown, the method for adjusting the first speech rate parameter also includes: step S505, adjusting the first speech rate parameter based on the user's setting record value for the playback speech rate. The user can set the playback speech rate of the intelligent voice device by himself through human-computer interaction. Optionally, the user's setting record value for the device playback speech rate can also be used as a reference item for adjusting the first speech rate parameter. Optionally, the user's setting record value for the device playback speech rate can be the user's most recent setting record value for the device playback speech rate, or it can be the average of the recorded values ​​set by the user in the past, which is not limited here.

[0062] Figure 5 Steps S501 to S504 and steps 506 to 507 are similar to the above embodiment and will not be described in detail here.

[0063] According to some embodiments, adjusting the first speaking rate parameter to determine the second speaking rate parameter includes: calculating the normal distribution mean of the user's historical speaking rate records, the user's set record value for the playback speaking rate, and the weighted average of the first speaking rate parameter to determine the third speaking rate parameter; and determining the second speaking rate parameter based on the third speaking rate parameter.

[0064] By setting different weights for the above three parameter values, the weighted average is calculated to obtain the third speech speed parameter. Optionally, considering the user's usage habits, a larger weight can be set for the setting record value of the playback speech speed. It is understandable that those skilled in the art can determine the weights of the above three parameter values ​​by themselves through experiments, and no limitation is made here.

[0065] Optionally, those skilled in the art may also adjust the first speech rate parameter based on the user's historical speech rate records and the user's setting record value for the playback speech rate in other ways, which are not limited here.

[0066] Therefore, on the basis of adjusting the playback speed according to the user's age group, the speed parameters are further adjusted through the user's historical speed record and the user's set record value for the playback speed, so that personalized adjustment of the playback speed for different users of the same age group can be achieved.

[0067] According to some embodiments, Figure 6As shown, based on the third speech rate parameter, determining the second speech rate parameter includes: step 601, in response to the difference between the third speech rate parameter and the user's setting record value for the playback speed not exceeding the second threshold, determining the third speech rate parameter as the second speech rate parameter; step 602, in response to the difference between the third speech rate parameter and the user's setting record value for the playback speed exceeding the second threshold, determining the setting record value as the second speech rate parameter.

[0068] The user's setting record value for the playback speech speed is further compared with the third speech speed parameter. If the adjusted third speech speed parameter is significantly different from the playback speech speed set by the user, the second speech speed parameter for playing the voice is set to the playback speech speed set by the user in consideration of the user's usage habits; if the adjusted third speech speed parameter is slightly different from the playback speech speed set by the user, the second speech speed parameter for playing the voice is set to the adjusted second speech speed parameter. The speech speed parameter adjusted by the above method can better meet the user's needs.

[0069] According to some embodiments, Figure 7 As shown, the method of adjusting the first speech rate parameter also includes: step 704, adjusting the first speech rate parameter based on the content category of the content to be broadcast. In daily use, the intelligent voice device will respond to the needs of the user and play knowledge content (such as professional knowledge explanations, recipes, tutorials, etc.) to the user, and these contents often require the user to understand. Therefore, when adjusting the device speech rate parameter, the device classifies and identifies the content to be played. When the content to be played is identified as knowledge content, the device speech rate parameter is appropriately reduced on the basis of the above adjustment. It is understandable that those skilled in the art can classify the content to be played by text classification methods such as naive Bayes classification algorithm, KNN, SVM, maximum entropy and neural network, which are not limited here.

[0070] Therefore, when playing knowledge-based content that requires user understanding, the playback speed can be appropriately reduced to help users better understand the playback content.

[0071] Figure 7 Steps S701 to S703 and steps 706 to 707 are similar to the above embodiment and will not be described in detail here.

[0072] According to another aspect of the present disclosure, a device 800 for an intelligent voice device is also provided. Figure 8As shown, it includes: a first determination unit 810, configured to determine the age range of the user based on the user's biometric characteristics; a selection unit 820, configured to select a preset first speech rate parameter for broadcasting voice based on the age range; a first adjustment unit 830, configured to adjust the first speech rate parameter based on the user's historical speech rate record in response to identifying the identity of the user, wherein the historical speech rate record includes a user-specific speech rate parameter extracted from the user's voiceprint feature in at least one interaction between the intelligent voice device and the user to determine a second speech rate parameter; and a broadcasting unit 840, configured to broadcast voice based on the second speech rate parameter.

[0073] The operations of units 810 to 840 of the apparatus 800 for an intelligent voice device are similar to the operations of steps S201 to S204 of the above-mentioned method for an intelligent voice device, and are not described in detail here.

[0074] According to some embodiments, the first determination unit is further configured to determine the age range of the user based on the facial features and voiceprint features of the user.

[0075] According to some embodiments, Fig. 9 As shown, the first determination unit 920 includes: a first determination subunit 921, configured to determine a first predicted age of a user based on facial features of the user; a second determination subunit 922, configured to determine a second predicted age of the user based on a voiceprint feature of the user; a third determination subunit 923, configured to determine that the age of the user is the first predicted age in response to a difference between the first predicted age and the second predicted age not exceeding a first threshold; a fourth determination subunit 924, configured to determine that the age of the user is the second predicted age in response to a difference between the first predicted age and the second predicted age exceeding a first threshold; and a fifth determination subunit 925, configured to determine an age range of the user based on the determined age of the user.

[0076] According to some embodiments, the first adjustment unit includes: a reading subunit, configured to read at least one historical speaking rate record of the user in response to identifying the identity of the user; a first calculation subunit, configured to perform normal distribution fitting on at least one historical speaking rate record to calculate the normal distribution mean of at least one historical speaking rate record; and a first adjustment subunit, configured to adjust the first speaking rate parameter based on the normal distribution mean.

[0077] According to some embodiments, the apparatus for an intelligent voice device further includes: a second adjustment unit configured to adjust the first speech rate parameter based on the recorded value set by the user for the playback speech rate.

[0078] According to some embodiments, the second adjustment unit is further configured to calculate the weighted average of the normal distribution mean, the user's set recorded value for the playback speed, and the first speed parameter to determine the third speed parameter; and determine the second speed parameter based on the third speed parameter.

[0079] According to some embodiments, the second adjustment unit also includes: a sixth determination subunit, configured to determine the third speech rate parameter as the second speech rate parameter in response to the difference between the third speech rate parameter and the user's set recorded value for the playback speech rate not exceeding a second threshold value; and a seventh determination subunit, configured to determine the set recorded value as the second speech rate parameter in response to the difference between the third speech rate parameter and the user's set recorded value for the playback speech rate exceeding the second threshold value.

[0080] According to some embodiments, Fig.10 As shown, the apparatus 1000 for an intelligent voice device further includes: a third adjustment unit 1050, configured to adjust the first speech rate parameter based on the content category of the content to be broadcast. The operations of units 1010-1040, unit 1060, subunits 1031-1033, and subunits 1041-1042 of the apparatus 1000 for an intelligent voice device are similar to the above operations and are not described in detail herein.

[0081] According to an embodiment of the present disclosure, an electronic device, a readable storage medium, a computer program product and an intelligent voice device are also provided.

[0082] refer to Fig.11 , a block diagram of an electronic device 1100 that can be used as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0083] like Fig.11As shown, the device 1100 includes a computing unit 1101, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1102 or a computer program loaded from a storage unit 1108 into a random access memory (RAM) 1103. In the RAM 1103, various programs and data required for the operation of the device 1100 can also be stored. The computing unit 1101, the ROM 1102, and the RAM 1103 are connected to each other via a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0084] Multiple components in the device 1100 are connected to the I / O interface 1105, including: an input unit 1106, an output unit 1107, a storage unit 1108, and a communication unit 1109. The input unit 1106 can be any type of device that can input information to the device 1100. The input unit 1106 can receive input digital or character information, and generate key signal input related to user settings and / or function control of the electronic device, and can include but is not limited to a mouse, a keyboard, a touch screen, a track pad, a track ball, a joystick, a microphone, and / or a remote controller. The output unit 1107 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1108 can include but is not limited to a disk and an optical disk. The communication unit 1109 allows the device 1100 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver and / or a chipset, such as a Bluetooth™ device, a 1302.11 device, a WiFi device, a WiMax device, a cellular communication device and / or the like.

[0085] The computing unit 1101 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1101 performs the various methods and processes described above, such as methods for intelligent voice devices. For example, in some embodiments, the method for an intelligent voice device may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1108. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1100 via ROM 1102 and / or communication unit 1109. When the computer program is loaded into RAM 1103 and executed by the computing unit 1101, one or more steps of the method for an intelligent voice device described above may be performed. Alternatively, in other embodiments, the computing unit 1101 may be configured to execute the method for the intelligent voice device in any other appropriate manner (for example, by means of firmware).

[0086] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0087] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0088] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0089] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0090] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0091] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0092] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0093] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but only by the claims after authorization and their equivalent scope. Various elements in the embodiments or examples can be omitted or replaced by their equivalent elements. In addition, each step can be performed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples can be combined in various ways. It is important that with the evolution of technology, many elements described herein can be replaced by equivalent elements that appear after the present disclosure.

Claims

1. A method for an intelligent voice device, comprising: Determining an age range of the user based on a biometric feature of the user; Based on the age range, selecting a preset first speech rate parameter for the voice broadcast; In response to identifying the identity of the user, adjusting the first speech rate parameter based on the historical speech rate record of the user to determine the second speech rate parameter, wherein the historical speech rate record includes a speech rate parameter specific to the user extracted from the voiceprint feature of the user in at least one interaction between the intelligent voice device and the user, wherein, in response to identifying the identity of the user, adjusting the first speech rate parameter based on the historical speech rate record of the user includes: In response to identifying the identity of the user, reading at least one historical speech rate record of the user; Performing normal distribution fitting on the at least one historical speech rate record to calculate a normal distribution mean of the at least one historical speech rate record; Based on the normal distribution mean, adjusting the first speech rate parameter; and Adjusting the first speech rate parameter based on the recorded setting value of the playback speech rate by the user; And wherein, adjusting the first speech rate parameter to determine the second speech rate parameter includes: Calculating a weighted average of the normal distribution mean, the setting record value, and the first speech rate parameter to determine a third speech rate parameter; and Based on the third speech rate parameter, determining the second speech rate parameter; and The speech is broadcast based on the second speech rate parameter.

2. The method according to claim 1, wherein: The biometric features include facial features and voiceprint features of the user.

3. The method according to claim 2, wherein: Determining the age range of the user based on the biometrics of the user includes: Determining a first predicted age of the user based on the facial feature of the user; determining a second predicted age of the user based on the voiceprint feature of the user; In response to a difference between the first predicted age and the second predicted age not exceeding a first threshold, determining the age of the user to be the first predicted age; In response to a difference between the first predicted age and the second predicted age exceeding a first threshold, determining the user's age to be the second predicted age; and Based on the determined age of the user, the age range of the user is determined.

4. The method according to claim 1, wherein: The determining the second speech rate parameter based on the third speech rate parameter includes: In response to a difference between the third speech rate parameter and the set record value not exceeding a second threshold, determining the third speech rate parameter as the second speech rate parameter; and In response to a difference between the third speech rate parameter and the set record value exceeding a second threshold, the set record value is determined as the second speech rate parameter.

5. The method according to any one of claims 1 to 3, further comprising: The first speech rate parameter is adjusted based on the content category of the content to be broadcast.

6. A device for an intelligent voice device, comprising: A first determining unit is configured to determine an age range of the user based on a biometric feature of the user; A selection unit is configured to select a preset first speech speed parameter for broadcasting speech based on the age range; A first adjustment unit is configured to adjust the first speech rate parameter based on a historical speech rate record of the user in response to identifying the identity of the user, wherein the historical speech rate record includes a speech rate parameter specific to the user extracted from the voiceprint feature of the user in at least one interaction between the intelligent voice device and the user to determine a second speech rate parameter, wherein the first adjustment unit includes: a reading subunit, configured to read at least one historical speech rate record of the user in response to identifying the identity of the user; a first calculation subunit, configured to perform normal distribution fitting on the at least one historical speech rate record to calculate a normal distribution mean of the at least one historical speech rate record; and A first adjustment subunit is configured to adjust the first speech rate parameter based on the normal distribution mean; A second adjustment unit is configured to adjust the first speech rate parameter based on the setting record value of the playback speech rate of the user; And wherein the second adjustment unit is further configured to calculate a weighted average of the normal distribution mean, the setting record value and the first speech rate parameter to determine a third speech rate parameter; and Based on the third speech rate parameter, determining the second speech rate parameter; and The broadcasting unit is configured to broadcast the speech based on the second speech rate parameter.

7. The device according to claim 6, wherein: The biometric features include facial features and voiceprint features of the user.

8. The device according to claim 7, wherein: The first determining unit includes: A first determining subunit is configured to determine a first predicted age of the user based on the facial features of the user; a second determining subunit, configured to determine a second predicted age of the user based on the voiceprint feature of the user; a third determining subunit, configured to, in response to a difference between the first predicted age and the second predicted age not exceeding a first threshold, determine that the age of the user is the first predicted age; a fourth determining subunit, configured to, in response to a difference between the first predicted age and the second predicted age exceeding a first threshold, determine that the age of the user is the second predicted age; and The fifth determining subunit is configured to determine the age range of the user based on the determined age of the user.

9. The device according to claim 6, wherein: The second adjustment unit further includes: A sixth determining subunit is configured to, in response to a difference between the third speech rate parameter and the set record value not exceeding a second threshold, determine the third speech rate parameter as the second speech rate parameter; and The seventh determining subunit is configured to determine the set record value as the second speech rate parameter in response to a difference between the third speech rate parameter and the set record value exceeding a second threshold.

10. The device according to any one of claims 6 to 8, further comprising: The third adjustment unit is configured to adjust the first speech rate parameter based on the content category of the content to be broadcast.

11. An electronic device, comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

12. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

13. A computer program product comprising a computer program, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

14. An intelligent voice device, comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method performed by the intelligent voice device in any one of claims 1-5.

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