CN109243464A - Speech recognition tools dispositions method, device, computer equipment and storage medium - Google Patents
Speech recognition tools dispositions method, device, computer equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/28—Constructional details of speech recognition systems
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Abstract
The invention discloses a kind of speech recognition tools dispositions methods, for solving the problem of speech recognition tools complex installation process and the time-consuming huge deployment and application for being unfavorable for speech recognition tools on different terminals.The method include that installing operating system mirror image on the application container engine of first terminal；Dependence packet needed for installing speech recognition tools and speech recognition tools on the operating system mirror image, obtains tool environment mirror image；It is exported on tool environment mirror image to the application container engine of second terminal by the application container engine of the first terminal, so that the engine-operated tool environment mirror image of the application container of the second terminal and work offer speech-recognition services.The present invention also provides a kind of speech recognition tools deployment device, computer equipment and storage mediums.
Description
Technical field
The present invention relates to technical field of voice recognition more particularly to a kind of speech recognition tools dispositions methods, device, calculating
Machine equipment and storage medium.
Background technique
Kaldi is a kind of powerful speech recognition tools, currently, many enterprises and research and development centre are all made of kaldi progress
The research and application of speech recognition.But the requirement due to the use of kaldi to system environments is more, in the language for building kaldi
When sound environment-identification, need to install numerous third side plugs and tool, such as cuda (Compute Unified Device
Architecture), gst (GStreamer, for constructing the open source multimedia framework of Stream Media Application), libatlas
(Automatic Tuned Linear Algebra Software) etc., complex installation process and time-consuming huge are unfavorable for
Deployment and application of the kaldi on different terminals.
Summary of the invention
Based on this, it is necessary to which in view of the above technical problems, providing a kind of can be improved speech recognition tools deployment efficiency
Speech recognition tools dispositions method, device, computer equipment and storage medium.
A kind of speech recognition tools dispositions method, comprising:
Operating system mirror image is installed on the application container engine of first terminal；
Dependence packet needed for installing speech recognition tools and speech recognition tools on the operating system mirror image, obtains
Tool environment mirror image；
Drawn by the application container that the application container engine of the first terminal exports tool environment mirror image to second terminal
It holds up, so that the engine-operated tool environment mirror image of the application container of the second terminal and work offer speech-recognition services.
A kind of speech recognition tools deployment device, comprising:
System image installs module, for installing operating system mirror image on the application container engine of first terminal；
Speech recognition tools install module, for installing speech recognition tools and voice on the operating system mirror image
Dependence packet needed for identification facility, obtains tool environment mirror image；
Environment mirror export module, for exporting tool environment mirror image extremely by the application container engine of the first terminal
On the application container engine of second terminal, so that the engine-operated tool environment mirror image of the application container of the second terminal is simultaneously
Speech-recognition services are provided.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize above-mentioned speech recognition tools deployment side when executing the computer program
The step of method.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
The step of calculation machine program realizes above-mentioned speech recognition tools dispositions method when being executed by processor.
Above-mentioned speech recognition tools dispositions method, device, computer equipment and storage medium, firstly, in first terminal
Operating system mirror image is installed on application container engine；Then, on the operating system mirror image install speech recognition tools and
Dependence packet needed for speech recognition tools, obtains tool environment mirror image；Then, pass through the application container engine of the first terminal
It exports on tool environment mirror image to the application container engine of second terminal, so that the application container of the second terminal is engine-operated
The tool environment mirror image and work offer speech-recognition services.As it can be seen that the present invention makes speech recognition by application container engine
The tool environment mirror image of tool, by having installed speech recognition tools and speech recognition tools institute in the tool environment mirror image
The dependence packet needed, to no longer need to install after the tool environment mirror image is directed on the application container engine of second terminal
Dependence packet needed for speech recognition tools or speech recognition tools can run the tool environment mirror image directly to provide voice and know
It does not service, avoids the speech recognition tools installation process cumbersome when disposing on different terminals, substantially increase such as kaldi
The deployment efficiency of such speech recognition tools, is conducive to the popularization and application of speech recognition tools.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is an application environment schematic diagram of speech recognition tools dispositions method in one embodiment of the invention；
Fig. 2 is a flow chart of speech recognition tools dispositions method in one embodiment of the invention；
Fig. 3 is stream of the speech recognition tools dispositions method step S102 under an application scenarios in one embodiment of the invention
Cheng Tu；
Fig. 4 is stream of the speech recognition tools dispositions method step S204 under an application scenarios in one embodiment of the invention
Cheng Tu；
Fig. 5 is that speech recognition tools dispositions method detects kaldi weight under an application scenarios in one embodiment of the invention
Fill the flow chart of number；
Fig. 6 is the structural schematic diagram of speech recognition tools deployment device in one embodiment of the invention；
Fig. 7 is a schematic diagram of computer equipment in one embodiment of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Speech recognition tools dispositions method provided by the present application, can be applicable in the application environment such as Fig. 1, wherein first
Terminal and second terminal are communicated by network with server.Wherein, first terminal and second terminal may include but unlimited
In various personal computers, laptop, smart phone, tablet computer and/or portable wearable device.Server can be with
It is realized with the server cluster of the either multiple server compositions of independent server.
It should be noted that for ease of description, the present invention is following will be with this typical speech recognition tools of kaldi
The particular content of the speech recognition tools dispositions method is described in detail as representing, those skilled in the art should be appreciated that
, content described below is applicable not only to kaldi, is applied equally to other speech recognition tools.
In one embodiment, it as shown in Fig. 2, providing a kind of speech recognition tools dispositions method, is applied in this way in Fig. 1
In server for be illustrated, include the following steps:
S101, operating system mirror image is installed on the application container engine of first terminal；
In the present embodiment, which, which will be easy engine, to be illustrated by taking docker as an example.Docker is oneOpen sourceAnswer
With container engine, allows developer that can be packaged their application and rely on packet into a transplantable container, then facilitate
Ground migrates these packed applications to other terminals.The present invention formally utilizes the working principle of docker, by kaldi journey
The dependence packet of sequence and kaldi are bundled to production kaldi environment mirror on docker, real by migrating the kaldi environment mirror
The rapid deployment of existing kaldi and migration.
Firstly, since kaldi could normally start dependent on system environments, therefore, in installation kaldi and production kaldi
Before mirror image, need that an operating system mirror image is installed on present docker.Operating system mentioned here can be Ubuntu,
Any one in the operating systems such as centos, oracle linux, windows.The operating system mirror image can pass through network
Downloading acquires, can also imprinting obtains directly from the terminal for be equipped with the operating system, this present embodiment is not limited
It is fixed.
It should be noted that the first terminal can refer to arbitrary two different terminals from following second terminals,
" first " and " second " is only the number for distinguishing two different terminals.In general, first terminal can be kaldi environment mirror
The source terminal of production, second terminal are then the target terminals for needing to carry out kaldi fast transferring, and therefore, first terminal is general
It is one, and second terminal can be one, two even more.This programme on a first terminal by making
The kaldi environment mirror can be loaded into more second terminals by kaldi environment mirror, realize kaldi fast transferring and
Deployment.
S102, speech recognition tools and speech recognition tools are installed on the operating system mirror image needed for dependence
Packet, obtains tool environment mirror image；
After installing operating system mirror image on docker, can be installed on the operating system mirror image kaldi and
Dependence packet needed for kaldi, obtains kaldi environment mirror, it is known that, which is located on docker, it comprises
The data and the relevant data of kaldi program (kaldi program and rely on packet) namely kaldi program of operating system mirror image with
And its environmental data relied on.
It should be noted that dependence packet needed for kaldi can specifically include apt-get, libtool, tornado, etc.
Deng.These rely on the installation kit of the program or service support that are relied on when packet refers to kaldi normal program operation, existing
Kaldi program also needs to install the normal load that just achievable kaldi is wrapped in these dependences during installation.Wherein, apt-get,
It is a linux order, the operating system of reason formula is assured suitable for deb, is mainly used for automatically from the software storage of internet
Search, installation, upgrading, uninstall or operating system, are for software package needed for installing kaldi；Libtool is main
One effect is the Dependence Problem for solving library during compile large software, and in the present embodiment, libtool is used to compile
Kaldi environment；Tornado is a kind of open source version of web server software, is used to handle the decoding environment of kaldi.
Further, as shown in figure 3, above-mentioned steps S102 can specifically include:
Dependence packet needed for S201, the installation kit for obtaining speech recognition tools and the speech recognition tools；
S202, the operating system mirror image is run on the application container engine of the first terminal to start object run
System；
S203, the installation kit that the speech recognition tools are installed on the destination OS；
S204, after the installation kit for successfully installing the speech recognition tools, according to needed for the speech recognition tools
Dependence packet default installation sequence the speech recognition tools successively and are one by one installed needed for dependence packet；
After S205, the dependence packet needed for successfully installing the speech recognition tools, determination obtains the tool environment
Mirror image.
For step S201, it is to be understood that dependence packet needed for the installation kit and kaldi of kaldi can pass through
Network is downloaded to obtain, or is prepared in advance by staff.In general, the installation kit of kaldi and dependence packet can make
It is prepared in advance before kaldi environment mirror, in the present solution, need to only prepare the installation kit of kaldi for first terminal and rely on packet
, need the terminal for each deployment kaldi to prepare the installation kit of a set of kaldi, rely on packet compared to the prior art, this
Scheme is undoubtedly easier, saves cost.
For step S202, it is known that, operating system mirror image is installed on the docker of the first terminal, is installed on docker
After operating system mirror image, the operating system mirror image can be directly run on docker, is equivalent to and starts the operating system, i.e.,
First operating system.
It only need to be as the installation procedure of existing kaldi, by kaldi after destination OS starting for step S203
Installation kit be installed on the destination OS.
For step S204, after the installation kit for successfully installing the kaldi, the dependence as needed for kaldi wraps it
Between generally there is stringent erection sequence, therefore, installation is also required to according to needed for the kaldi default of dependence packet when relying on packet
Erection sequence successively and one by one installs these and relies on packet, to guarantee to rely on the correct installation wrapped, reduces the abnormal situation of installation
Occur.
Further, as shown in figure 4, above-mentioned steps S204 can be specifically included:
S301, the default installation sequence that packet is relied on needed for the speech recognition tools is obtained；
S302, the dependence packet for determining sequence first in the default installation sequence are to be currently relied upon packet；
One duplication mirror image of the current destination OS of S303, production is as newest system image；
S304, packet is currently relied upon described in installation on current destination OS；
It is currently relied upon whether packet installs success described in S305, judgement, if described be currently relied upon packet install failure, executes step
If rapid S306 is currently relied upon whether packet installs success described, thens follow the steps S308；
S306, newest system image is run on the application container engine of the first terminal to restart target behaviour
Make system；
It is currently relied upon packet described in installation on S307, the destination OS after restart, returns to step S305；
Until S308, all dependence packets needed for the speech recognition tools are respectively mounted successfully, according to the default
Erection sequence determines that next dependence packet as packet is currently relied upon, returns to step S303.
For step S301, generally there is stringent erection sequence, therefore, server between dependence packet needed for kaldi
The erection sequence directly can be set as the default installation sequence in advance.
For step S302, needed in this method according to needed for the kaldi rely on packet default installation sequence successively and
Install one by one these rely on packet, therefore, first it is to be mounted rely on packet be exactly in the default installation sequence sort first according to
Rely packet, is wrapped as being currently relied upon.
For step S303, this method polluted the operating system mirror image on docker in order to avoid setup error,
Installation is each currently relied upon before packet, first makes a duplication mirror image of current destination OS as newest system mirror
Picture.In this way, when finding that some relies on packet setup error, the operation system state that can be directly retracted into before installing is improved
Stability when relying on packet needed for kaldi is installed.It should be noted that in this method after one dependence packet of every successfully installation,
Meeting return step S303 makes a newest system image, and the system image of newest production can cover previous system image,
It is equivalent to and records the newest operating system that successfully installation relies on packet, in this way after some dependence packet install failure, can move back
The last successful operation system state of installation is returned to, in the effect for guaranteeing to ensure installation while installing and rely on packet stability
Rate.
It, can be in current target after getting out the duplication mirror image of current destination OS for step S304
Packet is currently relied upon described in installation in operating system.
For step S305, it is to be understood that its program for having self-test after each dependence packet installation, it can be to service
The installation of device feedback whether successful information, server gets after the information it can be learnt that being currently relied upon whether packet installs success.
For step S306 and S307, it is to be understood that if described be currently relied upon packet install failure, in order to avoid this according to
Rely in packet installation process and brings pollution (such as residual installation file) to the destination OS and subsequent dependence packet is caused also to be pacified
Dress failure, this method restart object run by running newest system image on the docker of the first terminal
Destination OS is returned to the state before installation is currently relied upon packet by system.Then, the object run after restart
It is currently relied upon packet described in installation in system, then feeds back and executes step S305, whether installation is currently relied upon packet after judgement is restarted again
Success.
For step S308, it is to be understood that, can be according to the default if the packet that is currently relied upon is installed successfully
Erection sequence determines that next dependence packet as packet is currently relied upon, then returns to step S303 and continues to install other dependences
Packet, all dependence packets needed for the kaldi are respectively mounted success.
As shown in the above, S301-S308, this method may be implemented according to needed for the kaldi through the above steps
Dependence packet default installation sequence the kaldi successively and is one by one installed needed for dependence packet, to rely on packet steady guaranteeing to install
The efficiency of installation is also ensured while qualitative, to promote the success rate of server production kaldi environment mirror indirectly.
For step S205, after kaldi installation kit is successfully installed and relies on packet, in general, on docker
The environment mirror of kaldi is obtained, hence, it can be determined that obtaining the kaldi environment mirror.In the kaldi environment mirror
Operating system, kaldi program and kaldi needed for being packaged operation kaldi rely on packet.
It is disposed in view of the kaldi environment mirror will be supplied to other terminals (such as second terminal), therefore, is needed
The kaldi on destination OS is detected before deployment whether can normally start the safety to ensure subsequent kaldi deployment.
In the present embodiment, kaldi can be started on the destination OS, if starting is normal, illustrate the first terminal
Kaldi environment mirror energy normal use on docker, so that it is determined that obtaining the kaldi environment mirror；If starting failure,
Illustrate kaldi environment mirror on first terminal docker can not normal use, reinstall automatically kaldi installation kit and according to
Rely packet.Specifically, before determination obtains the kaldi environment mirror, this method can also include: that detection is grasped in the target
Make whether normally start kaldi in system, if it is not, S203 is then returned to step, if so, thening follow the steps S205.
Further, as shown in figure 5, before returning to step S203, this method can also include:
S401, accumulative speech recognition tools refitting number add 1；
S402, judge whether the speech recognition tools refitting number is more than preset threshold, if it is not, then returning to step
S203, if so, thening follow the steps S403；
The information of S403, feedback about the production failure of tool environment mirror image.
For step S401, kaldi refitting number reinstalls kaldi when being used to count this production kaldi mirror image
The number wrapped is relied on needed for program and kaldi.It is found that can not normally be opened on the destination OS whenever detecting
When dynamic kaldi, which, which resets number, adds up to add 1.It is understood that kaldi refitting number should be in due course
It resets, can be reset after this programme end of run, can also be fed back in step S403 and make failure about kaldi environment mirror
Information after reset, specifically can determine that the present embodiment be not construed as limiting this according to actual use situation.
For step S402 to S403, it is to be understood that if kaldi refitting number is excessive, it may be considered that this
The production failure of kaldi environment mirror avoids the operation resource for excessively consuming server, should inform that administrator stops in time, or
Person's server, which is automatically stopped, makes the kaldi environment mirror.Therefore, it is possible to judge that whether the kaldi refitting number is more than pre-
If threshold value, if kaldi refitting number is no more than preset threshold, it can return and execute above-mentioned steps S203；Conversely, if institute
Stating kaldi refitting number is more than preset threshold, then can feed back the information about the production failure of kaldi environment mirror, notice clothes
The administrator of business device carries out inspection processing.It should be noted that the preset threshold can be preset on the server, for example set
3 are set to, i.e., when kaldi refitting number is more than 3 times, then it is assumed that the production failure of this kaldi environment mirror.
As shown in the above, S401-S403, this method can be when kaldi refitting number be excessive through the above steps
It timely feedbacks, allows server administrators to learn at the first time and inspection in time is handled, avoid the operation money for excessively consuming server
Source.
S103, held by the application that the application container engine of the first terminal exports tool environment mirror image to second terminal
On device engine so that the engine-operated tool environment mirror image of the application container of the second terminal and provide speech recognition clothes
Business.
In the present solution, the export on the docker of first terminal can be passed through after determination obtains kaldi environment mirror
Function exports the kaldi environment mirror.It is understood that docker provide export apply mirror image function, these from
It can completely be imported on the docker of other terminals derived from docker is upper using mirror image, realize the fast transferring of application.
Docker this characteristic is exactly applied to the migration of kaldi, in deployment in a creative way by this programme, the derived kaldi environment
Mirror image can be fed on the docker of other terminals.
It is understood that directly kaldi can be exported by the docker of the first terminal when disposing kaldi
In environment mirror to the docker of second terminal, so that the docker of the second terminal runs the kaldi environment mirror simultaneously
Speech-recognition services are provided.It should be noted that second terminal here can with one, it is two or more, due to kaldi environment
Therefore total data needed for mirror image has contained kaldi operation imports the kaldi environment mirror to second terminal
After docker is upper, when needing to start kaldi, kaldi is directly run by the docker in second terminal, can be passed through
The interface of docker externally provides speech-recognition services.As it can be seen that fast transferring and the deployment of kaldi may be implemented in this programme, especially
It is when there are many second terminal quantity, and the method for this programme can save a large amount of time and human cost, so that largely
Second terminal can load in a short time kaldi program and externally provide speech-recognition services.
In the present embodiment, kaldi environment mirror is made by docker, due to having installed in the kaldi environment mirror
Dependence packet needed for kaldi and kaldi, thus by the kaldi environment mirror be directed on the docker of second terminal with
Dependence packet needed for no longer needing to installation kaldi or kaldi afterwards can run the kaldi environment mirror directly to provide voice and know
It does not service, avoids the kaldi installation process cumbersome when disposing on different terminals, substantially increase the deployment efficiency of kaldi,
Be conducive to the popularization and application of kaldi.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
In one embodiment, a kind of speech recognition tools deployment device is provided, the speech recognition tools dispose device with it is upper
Speech recognition tools speech recognition tools dispositions method in embodiment is stated to correspond.As shown in fig. 6, the speech recognition tools language
Sound identification facility deployment device includes that system image installation module 601, speech recognition tools installation module 602 and environment mirror are led
Module 603 out.Detailed description are as follows for each functional module:
System image installs module 601, for installing operating system mirror image on the application container engine of first terminal；
Speech recognition tools install module 602, on the operating system mirror image install speech recognition tools and
Dependence packet needed for speech recognition tools, obtains tool environment mirror image；
Environment mirror export module 603, for exporting tool environment mirror by the application container engine of the first terminal
On picture to the application container engine of second terminal, so that the engine-operated tool environment mirror of the application container of the second terminal
Picture simultaneously provides speech-recognition services.
Further, the speech recognition tools installation module may include:
First acquisition unit, for obtain speech recognition tools installation kit and the speech recognition tools needed for according to
Rely packet；
Os starting unit, for running the operating system mirror on the application container engine of the first terminal
As to start destination OS；
Speech recognition tools installation unit, for installing the peace of the speech recognition tools on the destination OS
Dress packet；
Packet installation unit is relied on, for after the installation kit for successfully installing the speech recognition tools, according to institute's predicate
Dependence needed for the default installation sequence of dependence packet needed for sound identification facility successively and one by one installs the speech recognition tools
Packet；
Determination unit determines described in obtaining after the dependence packet needed for successfully installing the speech recognition tools
Tool environment mirror image.
Further, the dependence packet installation unit may include:
Erection sequence obtains subelement, and the default installation for obtaining dependence packet needed for the speech recognition tools is suitable
Sequence；
It is currently relied upon packet and determines subelement, for determining that the dependence packet of sequence first in the default installation sequence is current
Rely on packet；
Image copying subelement, for making a duplication mirror image of current destination OS as newest system
Mirror image；
It is currently relied upon packet installation subelement, for being currently relied upon packet described in the installation on current destination OS；
Judgment sub-unit, for judging described be currently relied upon wraps whether install success；
First processing subelement, if the judging result for the judgment sub-unit be it is no, in the first terminal
Newest system image is run on application container engine to restart destination OS, and target behaviour after restart
Make to be currently relied upon packet described in installation in system, returns trigger the judgment sub-unit later；
Second processing subelement, if the judging result for the judgment sub-unit be it is yes, until the speech recognition
Before all dependence packets needed for tool are respectively mounted successfully, determine that next dependence packet is used as according to the default installation sequence and work as
Preceding dependence packet, returns and triggers the image copying subelement.
Further, the speech recognition tools installation module can also include:
Start detection unit, whether normally starts speech recognition tools on the destination OS for detecting；
Trigger unit is returned, it can not be normal on the destination OS if being detected for the starting detection unit
Start speech recognition tools, then returns to the triggering speech recognition tools installation unit；
Determination unit is triggered, is normally started on the destination OS if being detected for the starting detection unit
Speech recognition tools then return to the triggering determination unit.
Further, the speech recognition tools installation module can also include:
Number accumulated unit, can not be normal on the destination OS if detecting for the starting detection unit
Start speech recognition tools, accumulative speech recognition tools refitting number adds 1；
Frequency judging unit, for judging whether the speech recognition tools refitting number is more than preset threshold；
First trigger unit, if the judging result for the frequency judging unit be it is no, trigger return triggering
Unit；
Information feedback unit, if the judging result for the frequency judging unit be it is yes, feed back about tool environment
The information of mirror image production failure.
Specific restriction about speech recognition tools deployment device may refer to dispose above for speech recognition tools
The restriction of method, details are not described herein.Modules in above-mentioned speech recognition tools deployment device can be fully or partially through
Software, hardware and combinations thereof are realized.Above-mentioned each module can be embedded in the form of hardware or independently of the place in computer equipment
It manages in device, can also be stored in a software form in the memory in computer equipment, in order to which processor calls execution or more
The corresponding operation of modules.
In one embodiment, a kind of computer equipment is provided, which can be server, internal junction
Composition can be as shown in Figure 7.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
Data of the database of machine equipment for being related in storaged voice identification facility dispositions method.The network of the computer equipment connects
Mouth with external terminal by network connection for being communicated.To realize that a kind of voice is known when the computer program is executed by processor
Other tool dispositions method.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor realize speech recognition in above-described embodiment when executing computer program
The step of tool dispositions method, such as step S101 shown in Fig. 2 to step S103.Alternatively, processor executes computer program
The function of each module/unit of speech recognition tools deployment device in Shi Shixian above-described embodiment, such as module 601 shown in Fig. 6
To the function of module 603.To avoid repeating, which is not described herein again.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program realizes the step of speech recognition tools dispositions method in above-described embodiment when being executed by processor, such as shown in Fig. 2
Step S101 to step S103.Alternatively, realizing speech recognition tools in above-described embodiment when computer program is executed by processor
The function of each module/unit of device, such as module 601 shown in Fig. 6 are disposed to the function of module 603.To avoid repeating, here
It repeats no more.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of speech recognition tools dispositions method characterized by comprising
Operating system mirror image is installed on the application container engine of first terminal；
Dependence packet needed for installing speech recognition tools and speech recognition tools on the operating system mirror image, obtains tool
Environment mirror；
It is exported on tool environment mirror image to the application container engine of second terminal by the application container engine of the first terminal,
So that the engine-operated tool environment mirror image of the application container of the second terminal and work offer speech-recognition services.
2. speech recognition tools dispositions method according to claim 1, which is characterized in that described in the operating system mirror
The dependence packet as needed for upper installation speech recognition tools and speech recognition tools, obtaining tool environment mirror image includes:
Dependence packet needed for the installation kit of acquisition speech recognition tools and the speech recognition tools；
The operating system mirror image is run on the application container engine of the first terminal to start destination OS；
The installation kit of the speech recognition tools is installed on the destination OS；
After the installation kit for successfully installing the speech recognition tools, the dependence packet according to needed for the speech recognition tools
Dependence packet needed for default installation sequence successively and one by one installs the speech recognition tools；
After the dependence packet needed for successfully installing the speech recognition tools, determination obtains the tool environment mirror image.
3. speech recognition tools dispositions method according to claim 2, which is characterized in that described according to the speech recognition
Dependence packet needed for the default installation sequence wrapped successively and one by one installs the speech recognition tools is relied on needed for tool includes:
Obtain the default installation sequence of dependence packet needed for the speech recognition tools；
The dependence packet for determining sequence first in the default installation sequence is to be currently relied upon packet；
A duplication mirror image of current destination OS is made as newest system image；
Packet is currently relied upon described in installation on current destination OS；
It is currently relied upon whether packet installs success described in judgement；
If described be currently relied upon packet install failure, newest system mirror is run on the application container engine of the first terminal
Picture is currently relied upon packet described in installation on the destination OS after restart to restart destination OS, it
It returns to execute afterwards and is currently relied upon whether packet installs successful step described in judgement；
If the packet that is currently relied upon is installed successfully, all dependence packets needed for the speech recognition tools are respectively mounted success
Before, next dependence packet is determined as packet is currently relied upon according to the default installation sequence, it is current to execute production for return later
Destination OS a duplication mirror image as newest system image the step of.
4. speech recognition tools dispositions method according to claim 2 or 3, which is characterized in that obtain the work in determination
Before tool environment mirror, further includes:
Whether detection normally starts speech recognition tools on the destination OS；
If speech recognition tools can not normally be started on the destination OS by detecting, it is described described to return to execution
The step of installation kit of the speech recognition tools is installed on destination OS；
If detecting and normally starting speech recognition tools on the destination OS, executes determination and obtain the tool link
The step of border mirror image.
5. speech recognition tools dispositions method according to claim 4, which is characterized in that described described returning to execution
Before the step of installing the installation kit of the speech recognition tools on destination OS, further includes:
Accumulative speech recognition tools refitting number adds 1；
Judge whether the speech recognition tools refitting number is more than preset threshold；
If the speech recognition tools refitting number is no more than preset threshold, it is described in the destination OS to return to execution
The step of installation kit of the upper installation speech recognition tools；
If the speech recognition tools refitting number is more than preset threshold, the letter about the production failure of tool environment mirror image is fed back
Breath.
6. a kind of speech recognition tools dispose device characterized by comprising
System image installs module, for installing operating system mirror image on the application container engine of first terminal；
Speech recognition tools install module, for installing speech recognition tools and speech recognition on the operating system mirror image
Dependence packet needed for tool, obtains tool environment mirror image；
Environment mirror export module, for exporting the tool environment mirror image extremely by the application container engine of the first terminal
On the application container engine of second terminal, so that the engine-operated tool environment mirror image of the application container of the second terminal is simultaneously
Speech-recognition services are provided.
7. speech recognition tools according to claim 6 dispose device, which is characterized in that the speech recognition tools installation
Module includes:
First acquisition unit, for obtain speech recognition tools installation kit and the speech recognition tools needed for dependence
Packet；
Os starting unit, for run on the application container engine of the first terminal operating system mirror image with
Start destination OS；
Speech recognition tools installation unit, for installing the installation of the speech recognition tools on the destination OS
Packet；
Packet installation unit is relied on, for being known after the installation kit for successfully installing the speech recognition tools according to the voice
Dependence packet needed for the default installation sequence of dependence packet needed for other tool successively and one by one installs the speech recognition tools；
Determination unit, after the dependence packet needed for successfully installing the speech recognition tools, determination obtains the tool
Environment mirror.
8. speech recognition tools according to claim 7 dispose device, which is characterized in that the dependence packet installation unit packet
It includes:
Erection sequence obtains subelement, for obtaining the default installation sequence of dependence packet needed for the speech recognition tools；
It is currently relied upon packet and determines subelement, for determining that the dependence packet of sequence first in the default installation sequence is to be currently relied upon
Packet；
Image copying subelement, for making a duplication mirror image of current destination OS as newest system mirror
Picture；
It is currently relied upon packet installation subelement, for being currently relied upon packet described in the installation on current destination OS；
Judgment sub-unit, for judging described be currently relied upon wraps whether install success；
First processing subelement, if the judging result for the judgment sub-unit be it is no, in the application of the first terminal
Newest system image is run on container engine to restart destination OS, and the object run system after restart
It is currently relied upon packet described in installation on system, returns trigger the judgment sub-unit later；
Second processing subelement, if the judging result for the judgment sub-unit be it is yes, until the speech recognition tools
Before required all dependence packets are respectively mounted successfully, according to default installation sequence determine next dependences packet conduct currently according to
Rely packet, returns and trigger the image copying subelement.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of any one of 5 speech recognition tools dispositions method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realization speech recognition tools deployment side as described in any one of claim 1 to 5 when the computer program is executed by processor
The step of method.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810721797.2A CN109243464A (en) | 2018-07-04 | 2018-07-04 | Speech recognition tools dispositions method, device, computer equipment and storage medium |
| PCT/CN2018/106270 WO2020006880A1 (en) | 2018-07-04 | 2018-09-18 | Voice recognition tool deployment method, apparatus, computer device and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810721797.2A CN109243464A (en) | 2018-07-04 | 2018-07-04 | Speech recognition tools dispositions method, device, computer equipment and storage medium |
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| CN109243464A true CN109243464A (en) | 2019-01-18 |
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| WO (1) | WO2020006880A1 (en) |
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| CN114816550A (en) * | 2022-05-31 | 2022-07-29 | 浪潮(山东)计算机科技有限公司 | Computer operating system, software filling method and related components |
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| CN112527418A (en) * | 2020-12-11 | 2021-03-19 | 杭州安恒信息技术股份有限公司 | NPM packet acquisition method and device, electronic equipment and storage medium |
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