Information processing methods, systems and devices

Abstract

This application relates to the field of speech recognition technology, and discloses an information processing method, including: a first device node obtaining speech information and recognizing the speech information; if recognition fails, sending the speech information to a second device node on the same network segment so that the second device node can recognize the speech information; if the second device node successfully recognizes the speech information, obtaining the recognition result sent by the second device node. In this way, speech recognition can be achieved using the local speech information database of the second device node. Since device nodes on the same network segment can communicate directly, their communication distance is short, thus effectively reducing the response time of speech recognition and improving the user experience. This application also discloses an information processing system and an information processing device.

Description

Technical Field

[0001] This application relates to the field of speech recognition technology, and for example to an information processing method, system and apparatus. Background Technology

[0002] With advancements in technology and improvements in living standards, more and more people are paying attention to the development of smart homes. Currently, voice recognition technology has become a crucial step in human-computer interaction and is widely used in various home appliances. Specifically, home appliances can recognize the voice commands spoken by users, converting the vocabulary into computer-readable instructions, thereby enabling voice control of the appliances. Therefore, ensuring the accuracy of voice recognition has become a pressing issue that needs to be addressed.

[0003] To improve the accuracy of speech recognition, the prior art provides a speech recognition method, which includes: after receiving a command word, the local device performs recognition in a local database; if the local database does not store the command word, it sends the command word to the cloud for recognition; after receiving the command word, the cloud performs recognition in the cloud and returns the recognition result to the local device.

[0004] As can be seen, the above-mentioned speech recognition method can improve the accuracy of speech recognition by recognizing a large number of command words through interaction between local and cloud, with the help of the cloud's huge database. However, this solution has high requirements for the network. When the network latency is high, the response time of cloud speech recognition will be very long, which can easily affect the user experience. Summary of the Invention

[0005] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0006] This disclosure provides an information processing method, system, and apparatus to reduce the response time of speech recognition and improve the user experience.

[0007] In some embodiments, the information processing method includes: a first device node obtaining voice information and recognizing the voice information; if recognition fails, sending the voice information to a second device node in the same network segment so that the second device node can recognize the voice information; and if the second device node successfully recognizes the voice information, obtaining the recognition result sent by the second device node.

[0008] In some embodiments, the information processing method includes: a second device node located on the same network segment as the first device node obtains voice information, the voice information being sent by the first device node to the second device node in the event of recognition failure; recognizing the voice information, and sending the recognition result to the first device node if recognition is successful.

[0009] In some embodiments, the information processing system includes a first device node and a second device node located on the same network segment as the first device node. The first device node is configured to obtain voice information and recognize the voice information; if recognition fails, it sends the voice information to the second device node; the second device node is configured to recognize the voice information; if recognition is successful, it sends the recognition result to the first device node.

[0010] In some embodiments, the information processing apparatus includes a processor and a memory storing program instructions. The processor is configured to perform the information processing method described above when executing the program instructions.

[0011] The information processing methods, systems, and apparatuses provided in this disclosure can achieve the following technical effects:

[0012] If the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it succeeds, the first device node receives the recognition result. This interaction between the first and second device nodes on the same network segment, utilizing the second device node's local voice information database, enables voice recognition. Because device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to local-to-cloud communication, effectively reducing voice recognition response time and improving the user experience.

[0013] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0014] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0015] Figure 1 This is a schematic diagram of an information processing system provided in an embodiment of this disclosure;

[0016] Figure 2 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure;

[0017] Figure 3 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure;

[0018] Figure 4 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure;

[0019] Figure 5 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure;

[0020] Figure 6 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure;

[0021] Figure 7 This is a schematic diagram of an information processing device provided in an embodiment of the present disclosure. Detailed Implementation

[0022] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0024] Unless otherwise stated, the term "multiple" means two or more.

[0025] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0026] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0027] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0028] In this embodiment of the disclosure, smart home appliances refer to home appliances formed by introducing microprocessors, sensor technology and network communication technology into home appliances. They have the characteristics of intelligent control, intelligent sensing and intelligent application. The operation of smart home appliances often relies on the application and processing of modern technologies such as the Internet of Things, the Internet and electronic chips. For example, smart home appliances can be connected to electronic devices to enable users to remotely control and manage smart home appliances.

[0029] Figure 1 This is a schematic diagram of an information processing system provided in an embodiment of this disclosure. (In conjunction with...) Figure 1 As shown, this disclosure provides an information processing system that may include a first device node and a second device node located on the same network segment as the first device node. As an example, the first and second device nodes can be various smart home appliances with voice control functions. Both are connected to the same gateway node and are on the same network segment. Through mutual cooperation and the solution provided in this application embodiment, the first and second device nodes on the same network segment can interact, thereby achieving voice recognition by utilizing the local voice information database of the second device node.

[0030] In practical applications, users can input voice information into the first device node, which then uses its locally stored voice information database to recognize the corresponding command. If recognition fails, the first device node will send the voice information to a second device node on the same network segment.

[0031] Correspondingly, the second device node obtains the voice information and performs recognition. If recognition is successful, the second device node can send the recognition result to the first device node. In this way, the first device node can execute the command corresponding to the voice information. Thus, voice control can be achieved by using the second device node's local voice information database. Since the first and second device nodes on the same network segment can communicate directly over a short distance, the response time for voice recognition can be effectively reduced, improving the user experience. The specific implementation process is described below.

[0032] Figure 2 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure. (In conjunction with...) Figure 2 As shown, this disclosure provides an information processing method applicable to a first device node, which may include:

[0033] S21, the first device node obtains voice information and recognizes the voice information.

[0034] Here, the embodiments of this disclosure can provide a variety of implementation methods to enable the first device node to obtain and recognize voice information, as illustrated below.

[0035] In one approach, the first device node pre-sets voice wake-up information. The user can first input the voice wake-up information via voice, which the first device node then recognizes. Upon recognizing the voice wake-up information, the first device node triggers voice recognition and waits for the user to continue inputting voice information. Within a preset waiting time, the user can continue to input voice information, which the first device node then obtains and recognizes.

[0036] Here, the preset waiting time can be set to a range of 30 to 90 seconds.

[0037] In practical applications, the pre-set voice wake-up message for the first device node is "Hello, Xiaoyou." When the user says "Hello, Xiaoyou," the first device node can recognize the voice wake-up phrase, trigger voice recognition, and wait for the user to continue inputting voice information. Within 60 seconds, the user can continue to input voice information, such as "Please turn on," which the first device node can then obtain and recognize.

[0038] Alternatively, if the first device node is equipped with a control device, the user can directly operate the control device to trigger voice recognition. Here, the control device can be a remote control and / or a touchscreen. The user triggers voice recognition by pressing the mechanical button corresponding to the voice recognition function on the remote control and / or the virtual button corresponding to the voice recognition function on the touchscreen, and then waits for the user to continue inputting voice information. Within a preset waiting time, the user can continue to input voice information, which the first device node then obtains and recognizes.

[0039] Specifically, users can trigger voice recognition by pressing the button repeatedly within the initial press duration to set the number of presses. The initial press duration can range from 1 to 2 seconds, and the number of presses can range from 1 to 3.

[0040] Alternatively, users can trigger voice recognition by continuously pressing the button for a second duration. The second duration can range from 5 to 10 seconds.

[0041] In practical applications, the control device configured for the first device node takes a remote control with a mechanical button corresponding to voice recognition as an example. When the user presses the mechanical button three times consecutively within one second, or presses the mechanical button continuously for five seconds, the first device node can trigger voice recognition, waiting for the user to continue inputting voice information. Within 60 seconds, the user can continue to input voice information, such as "Please turn on," for the first device node to obtain and recognize.

[0042] Using the above method, the first device node can obtain and recognize voice information very conveniently and efficiently, thereby improving the intelligence level of the first device node and the user experience.

[0043] S22, if the first device node fails to recognize the voice information, it sends the voice information to the second device node in the same network segment so that the second device node can recognize the voice information.

[0044] Here, multiple second device nodes can be included within the same network segment.

[0045] In some embodiments, sending voice information to a second device node on the same network segment may include: the first device node simultaneously sending the voice information to multiple second device nodes so that the multiple second device nodes can simultaneously recognize the voice information.

[0046] In practical applications, multiple second device nodes are used, exemplified by nodes A, B, and C. The first device node can simultaneously send voice information to nodes A, B, and C, allowing them to perform voice recognition concurrently.

[0047] In some embodiments, sending voice information to a second device node in the same network segment may include: a first device node obtaining the voice information database capacity of each of the multiple second device nodes; the first device node determining the recognition priority of the multiple second device nodes according to the voice information database capacity; and the first device node sequentially sending the voice information to the multiple second device nodes in descending order of recognition priority, so that the multiple second device nodes can sequentially recognize the voice information.

[0048] Here, speech recognition is performed sequentially, which can be manifested as follows: if the second device node with the highest recognition priority successfully recognizes the speech, speech recognition stops; if the second device node with the highest recognition priority fails to recognize the speech, the next device node with the next highest recognition priority continues to recognize the speech, until all the second device nodes have completed their recognition.

[0049] Here, the recognition priority of multiple second device nodes corresponds to the capacity of the voice information database. This is because a larger voice information database increases the likelihood of successful recognition and improves recognition efficiency, thus giving it a higher priority. Sending voice information to multiple second device nodes sequentially according to their recognition priority helps ensure efficient and accurate voice recognition.

[0050] Specifically, the first device node can sort the voice information database capacities of multiple second device nodes in descending order, and use the sorting result as the recognition priority of the multiple second device nodes in descending order. That is, the second device node with the largest voice information database capacity has the highest recognition priority, and the second device node with the smallest voice information database capacity has the lowest recognition priority.

[0051] In practical applications, multiple second device nodes are used as examples, namely node A, node B, and node C. The voice information database capacity of node A is 5GB (gigabytes), that of node B is 2GB (gigabytes), and that of node C is 7GB (gigabytes). Therefore, the recognition priority of nodes A, B, and C, from highest to lowest, is node C, node A, and node B. Correspondingly, the first device node can sequentially send voice information to nodes C, A, and B for speech recognition.

[0052] S23, if the first device node successfully identifies the device, it obtains the identification result sent by the second device node.

[0053] In some embodiments, obtaining the recognition result sent by the second device node may include: when multiple second device nodes are simultaneously recognizing voice information, the first device node obtains the target recognition result sent by the target device node that first successfully recognized the information among the multiple second device nodes; the first device node sends a stop recognition command to the remaining second device nodes and uses the target recognition result as the recognition result sent by the second device nodes; wherein, the remaining second device nodes are the second device nodes other than the target device node. In this way, when multiple second device nodes are performing voice recognition simultaneously, the recognition result that was first successfully recognized can be obtained, thereby reducing the response time of voice recognition, improving the efficiency of voice recognition, and ensuring the user experience.

[0054] In practical applications, multiple second device nodes are used as examples, namely node A, node B, and node C. When nodes A, B, and C simultaneously recognize voice information, if node B successfully recognizes the information first, the first device node sends a stop recognition command to nodes A and C, and uses the recognition result of node B as the recognition result sent by the second device node.

[0055] In some embodiments, obtaining the recognition result sent by the second device node may include: when multiple second device nodes sequentially recognize the voice information according to their recognition priority from high to low, if the currently performing voice recognition by the first device node is successful, then the recognition result sent by the current second device node is taken as the recognition result sent by the second device node, and voice recognition is stopped. This can improve voice recognition efficiency while avoiding the waste of data processing resources caused by multiple second device nodes performing voice recognition.

[0056] In practical applications, multiple second device nodes are used as examples, namely node A, node B, and node C. The recognition priority of nodes A, B, and C, from highest to lowest, is node C, node A, and node B. Correspondingly, when the first device node performs speech recognition sequentially on nodes C, A, and B, if node C successfully recognizes the speech, the recognition result of node C is used as the recognition result sent by the second device node, and speech recognition stops. If node C fails to recognize the speech, the first device node sends voice information to node A for speech recognition.

[0057] In summary, using the information processing method provided in this embodiment, if the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it successfully recognizes it, the first device node receives the recognition result sent by the second device node. This allows interaction between the first and second device nodes on the same network segment, enabling voice recognition using the second device node's local voice information database. Since device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to communication between the local device and the cloud, effectively reducing the response time of voice recognition and improving the user experience.

[0058] Figure 3 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure. (In conjunction with...) Figure 3 As shown, this disclosure provides an information processing method applicable to a first device node, which may include:

[0059] S21, the first device node obtains voice information and recognizes the voice information.

[0060] S22, if the first device node fails to recognize the voice information, it sends the voice information to the second device node in the same network segment so that the second device node can recognize the voice information.

[0061] S23, if the first device node successfully identifies the device, it obtains the identification result sent by the second device node.

[0062] S31, if the first device node does not receive the recognition result sent by the second device node within the preset recognition time, it submits the voice information to the cloud node so that the cloud node can recognize the voice information.

[0063] Here, not receiving the identification result sent by the second device node can be interpreted as the second device node failing to identify, or as the second device node's response timeout.

[0064] Optionally, the preset recognition duration can be determined as follows: the first device node obtains the voice duration of the voice information; the first device node uses the recognition duration corresponding to the voice duration as the preset recognition duration according to a preset association relationship; wherein, the preset association relationship is the association relationship between the voice duration and recognition duration of different voice information. Since different voice durations may correspond to different recognition durations, this allows for the selection of a preset recognition duration for different voice durations while waiting for the second device node to send the recognition result, thereby improving the intelligence level of the first device node.

[0065] S32, if the first device node has successfully identified the device from the cloud node but has not yet received the identification result from the second device node, it sends a stop identification command to the second device node and receives the third identification result from the cloud node.

[0066] In summary, using the information processing method provided in this embodiment, if the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it successfully recognizes it, the first device node receives the recognition result. This allows interaction between the first and second device nodes on the same network segment, enabling voice recognition using the second device node's local voice information database. Since device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to local communication with the cloud, effectively reducing the response time for voice recognition and improving the user experience. Furthermore, if the second device node fails to recognize the voice information or times out, the voice information can be recognized using a cloud-based voice information database, further ensuring the accuracy of voice recognition and improving the intelligence level of the first device node.

[0067] Figure 4 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure. (In conjunction with...) Figure 4 As shown, this disclosure provides an information processing method applicable to a first device node, which may include:

[0068] S21, the first device node obtains voice information and recognizes the voice information.

[0069] S22, if the first device node fails to recognize the voice information, it sends the voice information to the second device node in the same network segment so that the second device node can recognize the voice information.

[0070] S23, if the first device node successfully identifies the device, it obtains the identification result sent by the second device node.

[0071] S31, if the first device node does not receive the recognition result sent by the second device node within the preset recognition time, it submits the voice information to the cloud node so that the cloud node can recognize the voice information.

[0072] S32, if the first device node has successfully identified the device from the cloud node but has not yet received the identification result from the second device node, it sends a stop identification command to the second device node and receives the third identification result from the cloud node.

[0073] S41, the first device node obtains the recognition frequency of the recognition results sent by the second device node and / or the recognition results sent by the cloud node.

[0074] S42, the first device node saves the recognition result if the recognition frequency is greater than or equal to the set frequency.

[0075] Here, the frequency can be set to a range of 5 to 10 times.

[0076] In summary, using the information processing method provided in this embodiment, if the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it successfully recognizes it, the first device node receives the recognition result sent by the second device node. This allows interaction between the first and second device nodes on the same network segment, enabling voice recognition using the second device node's local voice information database. Since device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to communication between the local device and the cloud, effectively reducing the response time of voice recognition and improving the user experience. Furthermore, if the second device node fails to recognize the voice information or times out, it can utilize a cloud-based voice information database to further ensure the accuracy of voice recognition. Moreover, by storing recognition results with a recognition frequency greater than or equal to a set frequency, the first device node can dynamically update its local voice information database, further enhancing its intelligence.

[0077] Figure 5 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure. (In conjunction with...) Figure 5As shown, this disclosure provides an information processing method applicable to a second device node, which may include:

[0078] S51, the second device node obtains voice information, which is sent by the first device node to the second device node in the event of recognition failure.

[0079] S52, the second device node recognizes the voice information and, if the recognition is successful, sends the recognition result to the first device node.

[0080] In summary, using the information processing method provided in this embodiment, if the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it successfully recognizes it, the first device node receives the recognition result sent by the second device node. This allows interaction between the first and second device nodes on the same network segment, enabling voice recognition using the second device node's local voice information database. Since device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to communication between the local device and the cloud, effectively reducing the response time of voice recognition and improving the user experience.

[0081] Figure 6 This is a schematic diagram of an information processing method provided in an embodiment of this disclosure. (In conjunction with...) Figure 6 As shown, this disclosure provides an information processing method that may include:

[0082] S61, the first device node obtains voice information and recognizes the voice information.

[0083] S62, if the first device node fails to recognize the voice information, it will send the voice information to the second device node in the same network segment.

[0084] S63, the second device node receives the voice information sent by the first device node.

[0085] S64, the second device node recognizes the voice information and, if the recognition is successful, sends the recognition result to the first device node.

[0086] S65, the first device node receives the identification result sent by the second device node.

[0087] In summary, using the information processing method provided in this embodiment, if the first device node fails to recognize the voice information, it can send the voice information to a second device node on the same network segment. The second device node then recognizes the voice information, and if it successfully recognizes it, the first device node receives the recognition result sent by the second device node. This allows interaction between the first and second device nodes on the same network segment, enabling voice recognition using the second device node's local voice information database. Since device nodes on the same network segment can communicate directly, the communication distance is significantly shortened compared to communication between the local device and the cloud, effectively reducing the response time of voice recognition and improving the user experience.

[0088] Figure 7 This is a schematic diagram of an information processing apparatus provided in an embodiment of this disclosure. (In conjunction with...) Figure 7 As shown, this disclosure provides an information processing apparatus, including a processor 100 and a memory 101. Optionally, the apparatus may further include a communication interface 102 and a bus 103. The processor 100, communication interface 102, and memory 101 can communicate with each other via the bus 103. The communication interface 102 can be used for information transmission. The processor 100 can call logical instructions stored in the memory 101 to execute the information processing method of the above embodiments.

[0089] Furthermore, the logic instructions in the aforementioned memory 101 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0090] The memory 101, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 100 executes functional applications and data processing by running the program instructions / modules stored in the memory 101, that is, it implements the information processing methods in the above embodiments.

[0091] The memory 101 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 101 may include high-speed random access memory and may also include non-volatile memory.

[0092] This disclosure provides a storage medium storing computer-executable instructions configured to perform the information processing method described above.

[0093] The aforementioned storage medium can be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0094] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0095] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0096] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0097] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0098] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. An information processing method characterized by comprising: include: The first device node obtains the voice information and recognizes the voice information; In the event of recognition failure, the voice information is sent to a second device node on the same network segment so that the second device node can recognize the voice information. The same network segment includes multiple second device nodes; sending the voice information to the second device nodes in the same network segment includes: Obtain the voice information database capacity of each of the plurality of second device nodes; according to the voice information database capacity, send the voice information to the plurality of second device nodes in sequence so that the plurality of second device nodes can identify the voice information in sequence, wherein identifying the voice information in sequence includes: in the case of identification failure, the second device node corresponding to the next identification priority continues to identify; If the second device node is successfully identified, the identification result sent by the second device node is obtained.

2. The method of claim 1, wherein, Based on the capacity of the voice information database, the voice information is sequentially sent to the plurality of second device nodes, so that the plurality of second device nodes sequentially recognize the voice information, including: Obtain the voice information database capacity of each of the plurality of second device nodes; Based on the capacity of the voice information database, the recognition priority of the plurality of second device nodes is determined; The voice information is sent to the plurality of second device nodes in descending order of recognition priority, so that the plurality of second device nodes can recognize the voice information in turn.

3. The method of claim 1, wherein, The same network segment includes multiple second device nodes, and obtaining the identification results sent by the second device nodes includes: When multiple second device nodes simultaneously recognize voice information, the target recognition result sent by the target device node that first successfully recognizes the voice information is obtained. Send a stop identification command to the remaining second device nodes, and use the target identification result as the identification result sent by the second device nodes; The remaining second device node refers to any second device node other than the target device node.

4. The method of claim 1, wherein, Also includes: If no recognition result is received from the second device node within the preset recognition time, the voice information is submitted to the cloud node so that the cloud node can recognize the voice information. If the cloud node identification is successful, but the identification result sent by the second device node is still not obtained, a stop identification command is sent to the second device node, and a third identification result sent by the cloud node is obtained.

5. The method of claim 4, wherein, The preset recognition time is determined in the following way: Obtain the duration of the voice information; According to the preset association relationship, the recognition duration corresponding to the voice duration is taken as the preset recognition duration; The preset association relationship is the relationship between the speech duration and recognition duration of different speech information.

6. The method of claim 4, wherein, Also includes: Obtain the identification frequency of the identification results sent by the second device node and / or the identification results sent by the cloud node; If the recognition frequency is greater than or equal to the set frequency, the recognition result is saved.

7. An information processing method characterized by comprising: include: A second device node located in the same network segment as the first device node obtains voice information. The voice information is sent sequentially to the multiple second device nodes in the same network segment by the first device node in the event of recognition failure, based on the voice information database capacity of each of the multiple second device nodes in the same network segment. The voice information is recognized, and if the recognition is successful, the recognition result is sent to the first device node; if the recognition fails, the voice information is sent to the second device node corresponding to the next recognition priority so that it can continue to recognize.

8. An information processing system, characterized by comprising: include: A first device node and a second device node located in the same network segment as the first device node, wherein the same network segment includes multiple second device nodes; The first device node is configured to acquire voice information and recognize the voice information; In the event of recognition failure, the voice information is sent to the second device node, including: obtaining the voice information database capacity of each of the plurality of second device nodes; and sequentially sending the voice information to the plurality of second device nodes according to the voice information database capacity, so that the plurality of second device nodes can sequentially recognize the voice information. The second device node is configured to recognize the voice information; if the recognition is successful, the recognition result is sent to the first device node; if the recognition fails, the voice information is sent to the second device node corresponding to the next recognition priority so that it can continue to recognize. 9.An information processing apparatus comprising a processor and a memory storing program instructions, the apparatus being configured to: The processor is configured to perform the information processing method as described in any one of claims 1 to 6 when executing the program instructions. 10.An information processing apparatus comprising a processor and a memory storing program instructions, the apparatus being configured to: The processor is configured to perform the information processing method as described in claim 7 when executing the program instructions.

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