Method and device for early warning voice broadcast
阅读说明：本技术 一种预警语音播报的方法和装置 (Method and device for early warning voice broadcast ) 是由 胡博超 于 2020-06-30 设计创作，主要内容包括：本发明公开了预警语音播报的方法和装置,涉及计算机技术领域。该方法的一具体实施方式包括获取预警信息,对预警信息中的每个字计算信息熵,进而计算得到每个字的信息熵值,如果信息熵值大于预设的信息熵阈值常量,则将该字标记为关键字,以将位于预警信息中相邻位置的关键字组成关键词；基于关键词对预警信息进行拆分,以得到每段只包括一个关键词且位于预警信息开头的多段预警信息,进而多段预警信息生成对应数量的语音播报线程；根据预设的时序模型,对所述语音播报线程进行叠加播报。从而,本发明的实施方式能够解决现有在播报时会错过大量重要语音信息的问题。(The invention discloses a method and a device for early warning voice broadcast, and relates to the technical field of computers. One specific implementation mode of the method comprises the steps of obtaining early warning information, calculating information entropy of each word in the early warning information, further calculating to obtain an information entropy value of each word, and marking the word as a keyword if the information entropy value is larger than a preset information entropy threshold constant so as to form the keyword by the keyword positioned at the adjacent position in the early warning information; splitting the early warning information based on the keywords to obtain multiple sections of early warning information, wherein each section of early warning information only comprises one keyword and is positioned at the beginning of the early warning information, and then generating voice broadcasting threads with corresponding quantity by the multiple sections of early warning information; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast. Therefore, the method and the device can solve the problem that a large amount of important voice information is missed in the existing broadcasting process.)
1. A method for early warning voice reporting is characterized by comprising the following steps:
acquiring early warning information, calculating information entropy of each word in the early warning information, further calculating to obtain an information entropy value of each word, and marking the word as a keyword if the information entropy value is larger than a preset information entropy threshold constant so as to form keywords at adjacent positions in the early warning information;
splitting the early warning information based on the keywords to obtain multiple sections of early warning information, wherein each section of early warning information only comprises one keyword and is positioned at the beginning of the early warning information, and then generating voice broadcasting threads with corresponding quantity by the multiple sections of early warning information;
and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
2. The method of claim 1, wherein obtaining the warning information comprises:
extracting transaction indexes in the early warning information;
and judging whether the transaction index is larger than the index threshold value or not based on a preset index threshold value, if so, calculating the information entropy of each word in the early warning information, and if not, discarding the early warning information.
3. The method of claim 2, wherein after calculating the information entropy for each word in the warning information, the method comprises:
recording the early warning information of the calculated information entropy as:
H(x)＝{h(x1),h(x2),…h(xn)}
wherein xi is the early warning information character, h (xi) is the information entropy of the character xi, and n is the total number of words;
setting an information entropy threshold constant as H, traversing the information entropy value H (xi) of each word obtained by calculation, and if H (xi) is larger than H, marking xi as a keyword; then, several keywords adjacent to each other in position form a keyword, and the early warning information is recorded as:
x＝{a,x1,x2,…xn,b,xn+1,xn+2,…xn+m,…}
wherein, a and b represent keywords, a ═ { a1, a2, … ai }, and b ═ b1, b2, … bj }; ai and bj represent keywords constituting the keyword, and xi represents non-keywords.
4. The method of claim 1, wherein calculating information entropy for each word in the pre-warning information comprises:
extracting one or more groups of target objects in the early warning information, and labeling each group of target objects based on the label type;
and calling a configuration engine to obtain a tag list corresponding to different tag types so as to calculate the information entropy of each word in the target object.
5. The method of claim 4, wherein calculating information entropy for each word in the early warning information comprises:
extracting one or more groups of target objects in the early warning information, and labeling a service name, an index name and a fixed description for each group of target objects;
calling a configuration engine, calculating information entropy for the early warning information with the label as the service name based on the service name full table, calculating information entropy for the early warning information with the label as the index name based on the index name list monitored by the system, and calculating the information entropy for the early warning information with the label as the fixed description according to the fixed description number preset by the system.
6. The method according to claim 1, wherein the overlaying broadcast of the voice broadcast thread according to a preset timing model comprises:
according to the splitting order of the early warning information, the voice broadcast threads are started in sequence, and the later voice broadcast thread is started when the broadcasting of the keywords of the early warning information in the previous voice broadcast thread is completed.
7. The method according to claim 6, wherein the overlaying broadcast of the voice broadcast thread comprises:
when the keywords of the early warning information in the previous voice broadcasting thread are broadcasted, but the non-keywords are not broadcasted yet, starting the next voice broadcasting thread to start broadcasting the next section of early warning information; the early warning information of the previous voice broadcast thread is finished along with the broadcast of the keywords, and the volume of the broadcast thread is gradually reduced along with the reduction of the information entropy until the whole broadcast of the residual content is completed.
8. The utility model provides a device of early warning voice broadcast which characterized in that includes:
the acquisition module is used for acquiring the early warning information, calculating the information entropy of each word in the early warning information, further calculating the information entropy value of each word, and marking the word as a keyword if the information entropy value is larger than a preset information entropy threshold constant so as to form the keyword by the keywords positioned at the adjacent positions in the early warning information;
the processing module is used for splitting the early warning information based on the keywords to obtain a plurality of sections of early warning information, wherein each section of early warning information only comprises one keyword and is positioned at the beginning of the early warning information, and then the plurality of sections of early warning information generate a corresponding number of voice broadcast threads; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for early warning voice broadcast.
Background
With the development of the asset management industry, the asset management scale and the investment business range are continuously expanded, in the business transaction (such as stock transaction), a trader needs to pay attention to the current fluctuation range of the entrusted report all the time, and the monitoring system provides the function of automatically broadcasting the early warning information by voice, reminds related personnel of paying attention to the market risk in the transaction process and carries out corresponding processing.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
due to the fact that market conditions change instantly, a large amount of early warning voice information needs to be broadcasted by the system in a short time in a time period when transactions are concentrated. In the traditional voice broadcasting method, the voice broadcasting information quantity is increased by accelerating the speed of speech, the increasing range is limited, and a system user can miss a large amount of important voice information.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for early warning voice broadcast, which can solve the problem that a large amount of important voice information is missed in the existing broadcast.
In order to achieve the above object, according to an aspect of the embodiments of the present invention, there is provided a method for early warning voice broadcast, including obtaining early warning information, calculating information entropy for each word in the early warning information, and further calculating to obtain information entropy of each word, and if the information entropy is greater than a preset information entropy threshold constant, marking the word as a keyword, so as to combine keywords located at adjacent positions in the early warning information into a keyword; splitting the early warning information based on the keywords to obtain multiple sections of early warning information, wherein each section of early warning information only comprises one keyword and is positioned at the beginning of the early warning information, and then generating voice broadcasting threads with corresponding quantity by the multiple sections of early warning information; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
Optionally, after the obtaining of the warning information, the method includes:
extracting transaction indexes in the early warning information;
and judging whether the transaction index is larger than the index threshold value or not based on a preset index threshold value, if so, calculating the information entropy of each word in the early warning information, and if not, discarding the early warning information.
Optionally, after calculating the information entropy for each word in the warning information, the method includes:
recording the early warning information of the calculated information entropy as:
H(x)＝{h(x1),h(x2),…h(xn)}
wherein xi is the early warning information character, h (xi) is the information entropy of the character xi, and n is the total number of words;
setting an information entropy threshold constant as H, traversing the information entropy value H (xi) of each word obtained by calculation, and if H (xi) is larger than H, marking xi as a keyword; then, several keywords adjacent to each other in position form a keyword, and the early warning information is recorded as:
x＝{a,x1,x2,…xn,b,xn+1,xn+2,…xn+m,…}
wherein, a and b represent keywords, a ═ { a1, a2, … ai }, and b ═ b1, b2, … bj }; ai and bj represent keywords constituting the keyword, and xi represents non-keywords.
Optionally, calculating an information entropy for each word in the warning information, including:
extracting one or more groups of target objects in the early warning information, and labeling each group of target objects based on the label type;
and calling a configuration engine to obtain a tag list corresponding to different tag types so as to calculate the information entropy of each word in the target object.
Optionally, calculating an information entropy for each word in the warning information, including:
extracting one or more groups of target objects in the early warning information, and labeling a service name, an index name and a fixed description for each group of target objects;
calling a configuration engine, calculating information entropy for the early warning information with the label as the service name based on the service name full table, calculating information entropy for the early warning information with the label as the index name based on the index name list monitored by the system, and calculating the information entropy for the early warning information with the label as the fixed description according to the fixed description number preset by the system.
Optionally, according to a preset time sequence model, the voice broadcast thread is overlaid and broadcasted, including:
according to the splitting order of the early warning information, the voice broadcast threads are started in sequence, and the later voice broadcast thread is started when the broadcasting of the keywords of the early warning information in the previous voice broadcast thread is completed.
Optionally, it is right that the voice broadcast thread carries out superposition broadcast, include:
when the keywords of the early warning information in the previous voice broadcasting thread are broadcasted, but the non-keywords are not broadcasted yet, starting the next voice broadcasting thread to start broadcasting the next section of early warning information; the early warning information of the previous voice broadcast thread is finished along with the broadcast of the keywords, and the volume of the broadcast thread is gradually reduced along with the reduction of the information entropy until the whole broadcast of the residual content is completed.
In addition, the invention also provides a device for broadcasting the early warning voice, which comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring the early warning information, calculating the information entropy of each word in the early warning information and further calculating the information entropy value of each word, and if the information entropy value is larger than the preset information entropy threshold constant, marking the word as a keyword so as to form the keywords at the adjacent positions in the early warning information into the keywords; the processing module is used for splitting the early warning information based on the keywords to obtain a plurality of sections of early warning information, wherein each section of early warning information only comprises one keyword and is positioned at the beginning of the early warning information, and then the plurality of sections of early warning information generate a corresponding number of voice broadcast threads; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
One embodiment of the above invention has the following advantages or benefits: the voice superposition broadcasting based on the keyword distribution obviously improves the voice information output quantity in unit time, can timely and completely broadcast the early warning information of the over-limit business transaction index monitored by the system to traders, and prevents the risk in advance and in the business transaction process.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of a method of early warning voice announcement according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a main flow of a method of early warning voice announcement according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of a main flow of a method of early warning voice announcement according to a third embodiment of the present invention;
fig. 4 is a schematic diagram of main modules of a warning voice broadcast apparatus according to an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a method for broadcasting an early warning voice according to a first embodiment of the present invention, where as shown in fig. 1, the method for broadcasting an early warning voice includes:
step S101, acquiring early warning information, calculating information entropy of each word in the early warning information, and marking keywords according to the information entropy.
In some embodiments, after the early warning information is obtained, the transaction index in the early warning information can be extracted. And then judging whether the transaction index is larger than the index threshold value or not based on a preset index threshold value, if so, calculating the information entropy of each word in the early warning information, and if not, discarding the early warning information. For example: and extracting stock transaction indexes in the early warning information, and if the stock transaction indexes are larger than a preset index threshold value, broadcasting the early warning information by voice.
As further embodiments, calculating the information entropy for each word in the early warning information includes:
and extracting a target object in the early warning information, labeling the target object based on the label type, and further calculating the information entropy of each word in the target object according to the label lists corresponding to different label types.
It should be noted that, one piece of warning information may include: one or more sets of business names (e.g., stock names), index names, fixed descriptions (e.g., "overrun"), such as "Yonghui Supermarket, Pufa Bank, cumulative upswing, overrun, Zhejiang securities, Zijin mining, I's deal percentage, overrun". That is, the service name, the index name, and the fixed description in the warning information are labeled, that is, the label (target object) includes three types, i.e., the service name, the index name, and the fixed description.
Further, when the information entropy of each word in the target object is calculated according to the tag lists corresponding to different tag types, the configuration engine may be called to obtain the corresponding tag list, so as to calculate the information entropy of each word in the target object.
The information entropy is a concept used for measuring the information quantity in the information theory. The more ordered a system is, the lower the information entropy is; conversely, the more chaotic a system is, the higher the entropy of the information becomes. Therefore, entropy can also be said to be a measure of the degree of system ordering. Formula of information entropy:
wherein: p (x)i) Represents a randomEvent xiThe probability of (c).
Preferably, for the early warning information with the label as the index name, the information entropy of each word in the index name can be calculated according to an index name list (i.e. a corresponding label list) monitored by the system.
For the early warning information with the label being the fixed description, the probability of the early warning information depends on the number of the fixed descriptions preset by the system, for example, if 2 fixed descriptions exist, the information entropy of each fixed description is 1.
For the early warning information with the label as the business name, the information entropy of each word in the business name can be calculated through a business name full table (such as a stock name full table obtained by an exchange and a deep crossing), for example, the business name is named as 'XX supermarket', and the information entropy of a first word 'X' is firstly calculated according to the stock name full table obtained by the exchange and the deep crossing. There is no information before the "X" word occurs, so the probability of the "X" word occurring is 1/4882(4882 is the total number of exchange stocks). Considering the requirement of the system on calculating the time delay, the information entropy calculation formula is simplified as follows:
h(x)＝-log2p(x)，
wherein: p (x) is the probability of occurrence of event x.
Substituting the probability of occurrence of the first word "X" into the above formula, the information entropy of "X" word was calculated to be 12.45. Then, the information entropy of the second word "X" is calculated, and the stock names obtained by the exchange and the deep exchange are searched in the whole table, and the stock starting with the first word "X" has 23 stocks, so that the probability of the second word "X" is 1/23, and the information entropy is 4.52. Finally, the information entropy of the two words of supermarket is 0, because there is only one stock starting with XX in all stock names.
It is worth mentioning that marking the keywords according to the information entropy includes:
traversing the information entropy value of each word obtained by calculation, and marking the word as a keyword if the information entropy value is larger than a preset information entropy threshold constant; and after traversing is finished, forming keywords at adjacent positions in the early warning information into keywords. Specifically, the method comprises the following steps:
recording the early warning information of the calculated information entropy as:
H(x)＝{h(x1),h(x2),…h(xn)}
wherein xi is the early warning information words, h (xi) is the information entropy of the words xi, and n is the total word number.
Setting an information entropy threshold constant as H, traversing the calculated information entropy value H (xi) of each word, and if H (xi) is greater than H, marking xi as a keyword. Then, several keywords adjacent to each other in position form a keyword, and the early warning information is recorded as:
x＝{a,x1,x2,…xn,b,xn+1,xn+2,…xn+m,…}
where, a and b represent keywords, a ═ a1, a2, … ai }, and b ═ b1, b2, … bj }. ai and bj represent keywords constituting the keyword, and xi represents non-keywords.
Step S102, splitting the early warning information based on the keywords to generate a corresponding number of voice broadcast threads according to the number of segments of the split early warning information; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
In some embodiments, the voice broadcast threads are overlaid and broadcasted according to a preset time sequence model, the voice broadcast threads can be sequentially started according to the splitting order of the early warning information, and the next voice broadcast thread is started when the broadcasting of the keywords of the early warning information in the previous voice broadcast thread is completed.
Preferably, the early warning information is split into a plurality of segments according to a splitting mode that each segment starts with a keyword and only comprises one keyword.
As another embodiment, when the voice broadcast threads are broadcast in a superposition manner, the broadcast volume of the voice broadcast threads is gradually reduced along with the reduction of the information entropy.
For example: according to the early warning information x ═ { a, x1,x2,…xn,b,xn+1,xn+2,…xn+m…, and the positions of the keywords a and b, the early warning information is split into multiple sections of early warning information. Each segment of the split early warning information only comprises a keyword and is positioned in the early warning informationBeginning of the message:
xa＝{a,x1,x2,…xn}
xb＝{b,xn+1,xn+2,…xn+m}
and generating voice broadcast threads with corresponding quantity according to the number of the split early warning information segments. When the keywords of the early warning information in the current voice broadcasting thread are completely broadcasted, but the non-keywords are not broadcasted yet, the system immediately starts the next voice broadcasting thread to start broadcasting the next section of early warning information, and the two sections of content are broadcasted simultaneously. Meanwhile, the early warning information of the previous voice broadcast thread is finished along with the broadcast of the keywords, and the volume of the broadcast thread is gradually reduced along with the reduction of the information entropy until the broadcast of all the residual contents is finished. The time sequence relation of multi-segment voice superposition broadcast is as follows:
broadcast thread/start time
t1
t2
t3
t4
t5
t6
…
Broadcast thread 1
a
x1
x2
…
xn
Broadcast thread 2
b
xn+1
xn+2
…
xn+m
……
In summary, the method for early warning voice broadcast provided by the invention enables a trader to normally execute other trades without staring at a monitoring screen all the time after starting the system in a trading period, and only needs to pay attention to the key information of the system voice broadcast. And if the early warning information needing to be processed is heard, the system monitoring screen is checked again, and possible transaction risks are identified.
Fig. 2 is a schematic diagram of a main flow of a warning voice broadcasting method according to a second embodiment of the present invention, where the warning voice broadcasting method may include:
step S201, acquiring early warning information, and extracting transaction indexes in the early warning information.
Step S202, determining whether the transaction index is greater than the index threshold value based on a preset index threshold value, if so, performing step S203, and if not, performing step S204.
Step S203, extracting a target object in the early warning information, labeling the target object based on the label type, further calculating the information entropy of each word in the target object according to the label list corresponding to different label types, and performing step S205.
And step S204, discarding the early warning information and exiting the process.
Step S205, traversing the information entropy value of each word obtained by calculation, and if the information entropy value is larger than a preset information entropy threshold constant, marking the word as a keyword.
And step S206, after the traversal is finished, forming keywords at adjacent positions in the early warning information into keywords.
And step S207, splitting the early warning information based on the keywords so as to generate a corresponding number of voice broadcast threads according to the number of segments of the split early warning information.
And S208, performing superposition broadcasting on the voice broadcasting thread according to a preset time sequence model.
Fig. 3 is a schematic diagram of a main flow of a method for early warning voice broadcasting according to a third embodiment of the present invention, where the method for early warning voice broadcasting may include:
step S301, acquiring early warning information, and extracting transaction indexes in the early warning information.
Step S302, determining whether the transaction index is greater than the index threshold value based on a preset index threshold value, if so, performing step S303, and if not, performing step S304.
Step S303, extracting a target object in the early warning information, labeling the target object based on the label type, further calculating the information entropy of each word in the target object according to the label lists corresponding to different label types, and performing step S305.
And step S304, discarding the early warning information and exiting the process.
And S305, traversing the information entropy value of each word obtained by calculation, and marking the word as a keyword if the information entropy value is larger than a preset information entropy threshold constant.
And step S306, after the traversal is finished, forming keywords at adjacent positions in the early warning information into keywords.
Step S307, splitting the early warning information into multiple segments according to a splitting mode that each segment starts with the keywords and only comprises one keyword, and generating corresponding number of voice broadcast threads.
And S308, sequentially starting voice broadcast threads according to the splitting sequence of the early warning information, and starting a next voice broadcast thread when the broadcasting of the keywords of the early warning information in the previous voice broadcast thread is finished.
Preferably, the broadcast volume of the voice broadcast thread is gradually reduced along with the reduction of the information entropy.
Fig. 4 is a schematic diagram of main modules of a warning voice broadcast apparatus according to an embodiment of the present invention, and as shown in fig. 4, the warning
In some embodiments, after the obtaining
extracting transaction indexes in the early warning information;
and judging whether the transaction index is larger than the index threshold value or not based on a preset index threshold value, if so, calculating the information entropy of each word in the early warning information, and if not, discarding the early warning information.
In some embodiments, the obtaining
and extracting a target object in the early warning information, labeling the target object based on the label type, and further calculating the information entropy of each word in the target object according to the label lists corresponding to different label types.
In some embodiments, after the obtaining
recording the early warning information of the calculated information entropy as:
H(x)＝{h(x1),h(x2),…h(xn)}
wherein xi is the early warning information character, h (xi) is the information entropy of the character xi, and n is the total number of words;
setting an information entropy threshold constant as H, traversing the information entropy value H (xi) of each word obtained by calculation, and if H (xi) is larger than H, marking xi as a keyword; then, several keywords adjacent to each other in position form a keyword, and the early warning information is recorded as:
x＝{a,x1,x2,…xn,b,xn+1,xn+2,…xn+m,…}
wherein, a and b represent keywords, a ═ { a1, a2, … ai }, and b ═ b1, b2, … bj }; ai and bj represent keywords constituting the keyword, and xi represents non-keywords.
In some embodiments, the obtaining
extracting one or more groups of target objects in the early warning information, and labeling each group of target objects based on the label type;
and calling a configuration engine to obtain a tag list corresponding to different tag types so as to calculate the information entropy of each word in the target object.
In some embodiments, the obtaining
extracting one or more groups of target objects in the early warning information, and labeling a service name, an index name and a fixed description for each group of target objects;
calling a configuration engine, calculating information entropy for the early warning information with the label as the service name based on the service name full table, calculating information entropy for the early warning information with the label as the index name based on the index name list monitored by the system, and calculating the information entropy for the early warning information with the label as the fixed description according to the fixed description number preset by the system.
In some embodiments, the
according to the splitting order of the early warning information, the voice broadcast threads are started in sequence, and the later voice broadcast thread is started when the broadcasting of the keywords of the early warning information in the previous voice broadcast thread is completed.
In some embodiments, the
when the keywords of the early warning information in the previous voice broadcasting thread are broadcasted, but the non-keywords are not broadcasted yet, starting the next voice broadcasting thread to start broadcasting the next section of early warning information; the early warning information of the previous voice broadcast thread is finished along with the broadcast of the keywords, and the volume of the broadcast thread is gradually reduced along with the reduction of the information entropy until the whole broadcast of the residual content is completed.
It should be noted that the method for early warning voice broadcast and the device for early warning voice broadcast according to the present invention have a corresponding relationship in the specific implementation content, and therefore the repeated content is not described again.
Fig. 5 shows an exemplary system architecture 500 to which the warning voice broadcasting method or the warning voice broadcasting apparatus according to the embodiment of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The terminal devices 501, 502, 503 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices having a screen for warning voice announcement and supporting web browsing, including but not limited to a smart phone, a tablet computer, a laptop portable computer, a desktop computer, and the like.
The server 505 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for warning voice broadcast provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, the computing device is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the computer system 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output section 607 including a speaker and the like such as a Cathode Ray Tube (CRT), a liquid crystal warning voice broadcast device (LCD), and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes an acquisition module and a processing module. Wherein the names of the modules do not in some cases constitute a limitation of the module itself.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs, and when the one or more programs are executed by the equipment, the equipment comprises the steps of acquiring early warning information, calculating information entropy of each word in the early warning information, and marking key words according to the information entropy; splitting the early warning information based on the keywords to generate a corresponding number of voice broadcast threads according to the number of segments of the split early warning information; and according to a preset time sequence model, the voice broadcast threads are overlaid and broadcast.
According to the technical scheme of the embodiment of the invention, the problem that a large amount of important voice information is missed in the existing broadcasting process can be solved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
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