CN111294060B - Voice information decoding method and device - Google Patents
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
- H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
- H03M13/23—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using convolutional codes, e.g. unit memory codes
- H03M13/235—Encoding of convolutional codes, e.g. methods or arrangements for parallel or block-wise encoding
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
- H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
- H03M13/05—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
- H03M13/09—Error detection only, e.g. using cyclic redundancy check [CRC] codes or single parity bit
Abstract
The disclosure relates to a method and a device for decoding voice information, wherein the method comprises the following steps: receiving input voice information, and performing convolutional code decoding on the voice information to obtain convolutional code decoding output bits; performing CRC; acquiring a symbol error rate; performing joint decoding inspection according to the CRC result and the symbol error rate; and closing the voice information receiving channel when the joint decoding test passes. The device comprises: the convolution code decoding unit is used for carrying out convolution code decoding on the voice information; a CRC check unit for performing CRC check; a symbol error rate acquisition unit configured to acquire a symbol error rate; the joint decoding inspection unit is used for joint decoding inspection; and the decoding control unit is used for closing the voice information receiving channel when the joint decoding test passes. By carrying out joint inspection based on the CRC result and the symbol error rate, the voice information decoding method and device can improve the reliability of the decoding result.
Description
Technical Field
The present disclosure relates to the field of voice communication, and in particular, to a method and apparatus for decoding voice information.
Background
In adaptive multi-rate (AMR, adaptive Multi Rate) voice traffic, in order to reduce the power consumption of the system, the received data may be decoded in advance and the corresponding Radio Frequency Integrated Circuit (RFIC) receive channels may be turned off in advance.
To determine when to shut down the RFIC, the received data may be decoded and cyclic redundancy (CRC, cyclic Redundancy Check) checked; if the CRC passes, closing the RFIC receiving channel so as to achieve the purpose of reducing power consumption.
However, due to the fact that the CRC check has false alarm, CRC check may be passed but decoding bits are wrong, in this case, the RFIC receiving channel is closed in advance, which may have a great influence on the system, such as occurrence of voice quality degradation and influence on user experience.
Disclosure of Invention
In view of this, the disclosure provides a method and apparatus for decoding voice information, which can improve the reliability of the decoding result.
According to a first aspect of the present disclosure, there is provided a speech information decoding method, the method comprising: receiving input voice information, and performing convolutional code decoding on the voice information to obtain convolutional code decoding output bits; decoding the output bit according to the convolutional code, and performing cyclic redundancy CRC (cyclic redundancy check); decoding output bits according to the voice information and the convolutional codes to obtain symbol error rate; performing joint decoding inspection according to the CRC result and the symbol error rate; and closing the voice information receiving channel when the joint decoding test passes.
In one possible implementation, decoding the output bits according to the speech information and the convolutional code to obtain a symbol error rate includes: performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits; obtaining comparison check bits according to the positive and negative states of the voice information; and comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
In one possible implementation manner, obtaining the comparison check bit according to the positive and negative states of the voice information includes: and marking positive sign information in the voice information as 0 bit, marking symbol information in the voice information as 1 bit, and obtaining comparison check bits.
In one possible implementation manner, the coding output bits and the comparison check bits are compared in sequence, and according to a comparison result, a symbol error rate is obtained, including: counting the total number M of bits of the coded output bits; comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N; the ratio N/M of the different number of bits N to the total number of bits M is used as the symbol error rate.
In one possible implementation, performing a joint decoding check according to the CRC check result and the symbol error rate includes: when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
In one possible implementation, the threshold is 0.25.
In one possible implementation, the convolutional code decoding includes Viterbi decoding.
In one possible implementation, the method further includes: when the joint decoding test fails, continuously receiving the input voice information; performing joint decoding inspection on the continuously received voice information; and closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
According to a second aspect of the present disclosure, there is provided a speech information decoding apparatus including: the convolution code decoding unit is used for receiving input voice information, performing convolution code decoding on the voice information, and obtaining convolution code decoding output bits; a cyclic redundancy CRC check unit, configured to decode output bits according to the convolutional code, and perform cyclic redundancy CRC check; the symbol error rate obtaining unit is used for obtaining the symbol error rate according to the voice information and the convolutional code decoding output bit; the joint decoding checking unit is used for performing joint decoding checking according to the CRC checking result and the symbol error rate; and the decoding control unit is used for closing the voice information receiving channel when the joint decoding test is passed.
In one possible implementation manner, the symbol error rate acquisition unit is configured to: performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits; obtaining comparison check bits according to the positive and negative states of the voice information; and comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
In a possible implementation manner, the symbol error rate obtaining unit is further configured to: and marking positive sign information in the voice information as 0 bit, marking symbol information in the voice information as 1 bit, and obtaining comparison check bits.
In a possible implementation manner, the symbol error rate obtaining unit is further configured to: counting the total number M of bits of the coded output bits; comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N; the ratio N/M of the different number of bits N to the total number of bits M is used as the symbol error rate.
In one possible implementation, the joint coding verification unit is configured to: when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
In one possible implementation, the threshold is 0.25.
In one possible implementation, the convolutional code decoding includes Viterbi decoding.
In one possible implementation, the decoding control unit is further configured to: when the joint decoding test fails, continuously receiving the input voice information; performing joint decoding inspection on the continuously received voice information; and closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
According to a third aspect of the present disclosure, there is provided a speech information decoding apparatus including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the method of the first aspect described above.
According to a fourth aspect of the present disclosure there is provided a non-transitory computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of the first aspect described above.
The method and the device for decoding the voice information can avoid the situation of CRC false alarm possibly happening as much as possible, thereby improving the reliability of the decoding result and further improving the quality of voice communication.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features and aspects of the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 shows a schematic diagram of an implementation of frame advance stop.
Fig. 2 shows a flowchart of a speech information decoding method according to an embodiment of the present disclosure.
Fig. 3 shows a flowchart of a speech information decoding method according to an embodiment of the present disclosure.
Fig. 4 shows a flow chart of an alternative probing method according to an embodiment of the present disclosure.
Fig. 5 shows a flowchart of a speech information decoding method according to an embodiment of the present disclosure.
Fig. 6 shows a block diagram of a speech information decoding apparatus according to an embodiment of the present disclosure.
Fig. 7 shows a schematic diagram of an example of an application according to the present disclosure.
Fig. 8 shows a block diagram of a speech information decoding apparatus according to an embodiment of the present disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the disclosure will be described in detail below with reference to the drawings. In the drawings, like reference numbers indicate identical or functionally similar elements. Although various aspects of the embodiments are illustrated in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
In addition, numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art have not been described in detail in order not to obscure the present disclosure.
In the case of AMR voice traffic, the dedicated transport channel (DTCH, dedicated Transmission Channel) of the physical layer carries AMR voice traffic, and in one possible case, the DTCH corresponds to a transmission time interval tti=20 ms,1 radio frame=10 ms, with 15 slots in each radio frame. Based on the characteristics of three voice frame formats under AMR voice service, the three voice frame formats are respectively a voice frame, a Silence Indicator (SID) frame and a null frame, and under the condition that only voice service and signaling service exist in a wideband code division multiple access (WCDMA, wideband Code Division Multiple) system and the like, decoding processing can be started in advance, and correspondingly, frame advance stop (FET, frame Early Termination) can be realized.
Fig. 1 shows an implementation of frame early stop, as shown, one possible implementation of a FET may be: decoding the received receipt and performing CRC (cyclic redundancy check) from the 9 th time slot of the 1 st radio frame; if the CRC passes, closing the RFIC receiving channel so as to achieve the purpose of reducing power consumption.
In the scheme, the voice service ClassA/B/C is mapped to DTCH0/1/2 respectively, the total number of the transmission channels is 3, the common CRC length on the DTCH0 is 12, and the CRC length on the DTCH1/2 is 0. The above scheme judges whether to turn off the RFIC according to whether the CRC passes or not, however, due to the existence of a false alarm in the CRC, the false alarm herein may refer to a phenomenon that the CRC passes but the decoding bits are wrong, and the probability of occurrence of the false alarm is higher when the CRC length is smaller. Therefore, whether the RFIC is closed or not is judged only by the CRC result, so that the influence on the voice communication system is large, the voice quality is reduced, the user experience is influenced, and the like.
In order to solve the above-mentioned problems, the present embodiment discloses an application example of a voice information decoding method, in this example, after receiving input voice information, the voice communication system may decode the received data and perform CRC check, meanwhile, the voice communication system may calculate a symbol error rate (SER, symbol Error Rate) of the received data, and perform joint judgment according to the CRC check result and the calculation result of SER to judge whether advanced decoding is successful, in this application example, when CRC check is successful and the value of SER is lower than a preset threshold value, advanced decoding may be considered to be successful, at this time, the voice communication system may close the RFIC receiving channel in advance to achieve the purpose of saving power consumption, if advanced decoding is unsuccessful, may continue to receive the input voice information, and try the above-mentioned process again until it is judged that advanced decoding is successful or that voice information is completely received.
Fig. 2 shows a flowchart of a speech information decoding method according to an embodiment of the present disclosure. The method may be performed by a user equipment, as shown, the method may comprise:
step S11, receiving the input voice information, and performing convolutional code decoding on the voice information to obtain convolutional code decoding output bits.
Step S12, decoding the output bit according to the convolution code, and performing cyclic redundancy CRC check.
And S13, decoding the output bits according to the voice information and the convolutional codes to obtain the symbol error rate.
And step S14, carrying out joint decoding inspection according to the CRC check result and the symbol error rate.
Step S15, when the joint decoding test is passed, the voice information receiving channel is closed.
The ue performing the above method may operate in a communication system for performing voice communication, and the specific type of the communication system is not limited, and may be a long term evolution (LTE, long Term Evolution) system, a WCDMA system, or a Time Division-synchronization code Division multiple access (TD-SCDMA, time Division-Synchronous Code Division Multiple Access) system, etc. The specific data form of the received input voice information is not limited, and may be raw data, or may be data to be decoded obtained through some processing procedure in the system, and in a possible implementation manner, the input voice information may be decoding input soft information for performing convolutional code decoding. In the above steps, the specific implementation manner of the convolutional code decoding is not limited, and the corresponding convolutional code decoding manner may be selected according to the actual situation, and in one possible implementation manner, the convolutional code decoding may be Viterbi (Viterbi) decoding.
Through the above steps, it can be seen that in this example, in the process of decoding voice information, besides decoding received voice information data and performing CRC check, symbol error rates SER, SER of the decoded data are counted, so that error conditions of decoded bits can be reflected, and false alarm conditions can be checked by CRC as much as possible, so that the time for closing the voice information receiving channel is more accurate, thereby improving reliability of decoding results, and achieving the purpose of reducing system power loss without affecting performance of the voice communication system.
As can be seen from the above steps, in order to improve the accuracy of decoding, the specific acquisition mode of the SER is not limited, and any method that can count the SER may be applied to this embodiment. Fig. 3 shows a flowchart of a speech information decoding method according to an embodiment of the present disclosure, as shown in the drawing, in a possible implementation, step S13 may include:
s131, performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits.
S132, obtaining comparison check bits according to the positive and negative states of the voice information.
S133, comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
Because the accuracy of the decoding result is to be judged, the decoded result, namely the convolution code decoded output bit, can be subjected to inverse convolution code encoding to obtain the encoded output bit, the obtained encoded output bit is compared with the content before decoding, namely the received voice information, and then the symbol error rate is obtained according to the comparison result. In this example, the implementation of the convolutional code encoding is not particularly limited, and in one example, the implementation of the convolutional code encoding may be a reverse operation of the implementation of the convolutional code decoding, since the purpose of the convolutional code encoding is to reverse encode the convolutional code decoding output bits.
Since the received voice information may not be in the form of binary codes, in the process of obtaining the symbol error rate through comparison, certain processing needs to be performed on the received voice information to obtain comparison check bits for comparison. The specific implementation manner of obtaining the comparison check bit is not limited by fixing, and can be binary coding of the voice information according to a certain mode or 01 coding statistics according to the positive and negative states of the voice information, so that the comparison check bit is obtained. Thus in one possible implementation, the implementation of step S132 may be: and marking positive sign information in the voice information as 0 bit, marking symbol information in the voice information as 1 bit, and obtaining comparison check bits. In one possible implementation, the implementation procedure of step S132 may also be: and marking positive sign information in the voice information as 1 bit, marking symbol information in the voice information as 0 bit, and obtaining comparison check bits. The process of obtaining the comparison check bit is simpler according to the positive and negative states of the voice information, is easy to realize, and does not influence the processing speed of the voice communication system.
The method for obtaining the comparison check bit can have various forms, and the specific obtaining process of the symbol error rate can also have certain change correspondingly, so the specific obtaining process of the symbol error rate is not limited, and any calculating mode capable of being used for counting the symbol error rate can be used as the corresponding obtaining process. Fig. 4 is a flowchart illustrating a speech information decoding method according to an embodiment of the present disclosure, and as shown in the drawing, in a possible implementation, step S133 may include:
s1331, counting the total number M of bits of the coded output bits.
S1332, comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N.
S1333, the ratio N/M of the different bit numbers N and the total bit number M is used as the symbol error rate.
Through the steps, the symbol error rate of the convolutional code decoding output bit can be counted as soon as possible in a simpler and rapid mode, and the counting result is accurate, so that the accuracy of the subsequent joint decoding inspection process can be improved, the decoding accuracy of the system is further improved, and the communication performance of the system is ensured.
After the CRC checksum is completed and the symbol error rate is obtained, joint decoding inspection may be performed according to the CRC checksum and the symbol error rate, and the specific implementation process of the joint decoding inspection is not limited in particular, and any joint decoding inspection manner meeting the conditions may be applied in this embodiment. In one possible implementation manner, the implementation manner of step S14 may be: when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
In the implementation form of the step S14, the threshold value of the symbol error rate is manually specified data, and may be flexibly selected according to the actual situation, so the value of the threshold value is not specifically limited. In one possible implementation, the specific value of the threshold may be chosen between 0.1 and 0.4. In one possible implementation, the threshold value may be 0.25.
In the above step, if the joint decoding test is passed, the voice information receiving channel may be closed correspondingly in advance, and if the joint decoding test is not passed, the voice information receiving channel may not be closed in advance. However, since the reliability of the decoding result may vary with the communication process, whether the voice information receiving channel is closed or not may also vary with the variation of the reliability of the decoding result. Fig. 5 is a flowchart of a method for decoding voice information according to an embodiment of the disclosure, where, as shown in the drawing, in a possible implementation manner, the method for decoding voice information may further include:
s16, when the joint decoding test fails, the input voice information is continuously received.
S17, carrying out joint decoding test on the continuously received voice information.
S18, closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
It can be seen from the above steps that when the joint decoding test fails, the input voice information can be continuously received, and the joint decoding test is performed on the voice information which is continuously received according to any one of the possible joint decoding test modes, if the joint decoding test passes, the voice information receiving channel can be closed, and if the joint decoding test does not pass, the above process can be repeated until the joint decoding test passes, or the voice information is completely received.
Therefore, through the joint verification mode, the time for closing the voice information receiving channel can be accurately judged. If the joint decoding check is passed, namely the CRC check is passed and the SER is lower than the threshold value, the decoding result can be proved to be accurate, at the moment, the voice information receiving channel is closed, the communication quality of the voice communication system is not reduced, and meanwhile, the functional loss of the system can be reduced; if the joint decoding test fails, one possible case may be that the CRC check fails, and it is known by the related art that the voice information receiving channel should not be closed in advance at this time, and another possible case may be that the CRC check fails but the SER exceeds or equals to the threshold, which may indicate that the decoding result is inaccurate, and if the voice information receiving channel is closed, the communication quality of the voice communication system is degraded due to the inaccurate decoding result, so that the communication experience of the user is affected, and therefore, the voice information receiving channel is not closed any more at this time. In summary, by the method, the communication performance of the system can be ensured, and the functional loss of the system can be reduced as much as possible under the condition that the user experience is not reduced.
Fig. 6 shows a block diagram of a speech information decoding apparatus according to an embodiment of the present disclosure, as shown, the apparatus 20 includes:
a convolutional code decoding unit 21, configured to receive input voice information, perform convolutional code decoding on the voice information, and obtain convolutional code decoded output bits;
a cyclic redundancy CRC check unit 22 for performing cyclic redundancy CRC check based on the convolutional code decoded output bits;
a symbol error rate obtaining unit 23, configured to obtain a symbol error rate according to the speech information and the convolutional code decoding output bits;
a joint decoding checking unit 24, configured to perform joint decoding checking according to the CRC check result and the symbol error rate;
the decoding control unit 25 is configured to close the voice information receiving channel when the joint decoding test is passed.
In one possible implementation, the symbol error rate acquisition unit is configured to: performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits; obtaining comparison check bits according to the positive and negative states of the voice information; and comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
In one possible implementation, the symbol error rate acquisition unit is further configured to: and marking positive sign information in the voice information as 0 bit, marking symbol information in the voice information as 1 bit, and obtaining comparison check bits.
In one possible implementation, the symbol error rate acquisition unit is further configured to: counting the total number M of bits of the coded output bits; comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N; the ratio N/M of the different number of bits N to the total number of bits M is used as the symbol error rate.
In one possible implementation, the joint decoding verification unit is configured to: when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
In one possible implementation, the threshold is 0.25.
In one possible implementation, the convolutional code decoding includes Viterbi decoding.
In one possible implementation, the decoding control unit is further configured to: when the joint decoding test fails, continuously receiving the input voice information; performing joint decoding inspection on the continuously received voice information; and closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
Fig. 7 shows a schematic diagram of an application example of the present disclosure, which is merely for facilitating understanding of the embodiments of the present disclosure, and is not limiting of the embodiments of the present disclosure.
As shown in fig. 7, after receiving the decoded input soft information, the voice communication system first performs Viterbi decoding on the decoded input soft information by using a Viterbi decoder, and outputs a decoding result, where the output decoding result is used for performing CRC check on the one hand, and the output decoding result is used for performing SER calculation on the other hand. In this application example, the calculating manner of SER may be: firstly, carrying out convolutional code encoding on a decoding result of a Viterbi decoder, simultaneously taking signs of decoding input soft information as 0 bit and 1 bit respectively, carrying out corresponding conversion on the decoding input soft information to obtain a corresponding conversion result, then sequentially comparing an output result after convolutional code encoding with the conversion result, and counting different bit numbers N and total bit numbers M, wherein the final calculation result of SER is SER=N/M. After the CRC result and the SER result are obtained respectively, the CRC result and the SER result can be judged in a combined way to determine whether the advanced decoding is successful or not, and after the combined judgment, the voice communication system is controlled to perform corresponding operation in other control modes. In this example, other ways of control may be: if the CRC passes and the SER is lower than a preset threshold value of 0.25, the early decoding is considered successful, otherwise, the early decoding is considered failed. In this example, when the early decoding is successful, the voice information receiving channel may be closed, so as to achieve the purpose of saving power consumption, if the early decoding fails, a part of data may be continuously received, and the decoding process may be attempted again until the early decoding is successful or the data reception is completed.
Fig. 8 is a block diagram illustrating a speech information decoding apparatus 1300 according to an exemplary embodiment, for example, apparatus 1300 may be provided as a server. Referring to fig. 8, apparatus 1300 includes a processing component 1322 that further includes one or more processors and memory resources represented by memory 1332 for storing instructions, such as application programs, executable by processing component 1322. The applications stored in memory 1332 may include one or more modules each corresponding to a set of instructions. Further, processing component 1322 is configured to execute instructions to perform the methods described above.
The apparatus 1300 may also include a power component 1326 configured to perform power management of the apparatus 1300, a wired or wireless network interface 1350 configured to connect the apparatus 1300 to a network, and an input output (I/O) interface 1358. The apparatus 1300 may operate based on an operating system stored in the memory 1332, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 1332, including computer program instructions executable by processing component 1322 of apparatus 1300 to perform the above-described methods.
The present disclosure may be a system, method, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
Computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts 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 disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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 foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (18)
1. A method for decoding speech information, the method comprising:
receiving input voice information, and performing convolutional code decoding on the voice information to obtain convolutional code decoding output bits;
decoding the output bit according to the convolutional code, and performing cyclic redundancy CRC (cyclic redundancy check);
decoding output bits according to the voice information and the convolutional codes to obtain symbol error rate;
performing joint decoding inspection according to the CRC result and the symbol error rate;
and closing the voice information receiving channel when the joint decoding test passes.
2. The method of decoding speech information according to claim 1, wherein decoding output bits from the speech information and the convolutional code to obtain a symbol error rate comprises:
performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits;
obtaining comparison check bits according to the positive and negative states of the voice information;
and comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
3. The method for decoding voice information according to claim 2, wherein obtaining the comparison check bit according to the positive and negative states of the voice information comprises:
and marking positive sign information in the voice information as 0 bit, marking negative sign information in the voice information as 1 bit, and obtaining comparison check bits.
4. The method for decoding voice information according to claim 2, wherein comparing the encoded output bits and the comparison check bits in sequence, and obtaining a symbol error rate according to the comparison result, comprises:
counting the total number M of bits of the coded output bits;
comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N;
the ratio N/M of the different number of bits N to the total number of bits M is used as the symbol error rate.
5. The speech information decoding method of claim 1, wherein performing joint decoding verification based on the result of the CRC check and the symbol error rate comprises:
when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
6. The method of claim 5, wherein the threshold is 0.25.
7. The method of claim 1, wherein the convolutional code decoding comprises Viterbi decoding.
8. The method for decoding voice information according to claim 1, further comprising:
when the joint decoding test fails, continuously receiving the input voice information;
performing joint decoding inspection on the continuously received voice information;
and closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
9. A speech information decoding apparatus, comprising:
the convolution code decoding unit is used for receiving input voice information, performing convolution code decoding on the voice information, and obtaining convolution code decoding output bits;
a cyclic redundancy CRC check unit, configured to decode output bits according to the convolutional code, and perform cyclic redundancy CRC check;
the symbol error rate obtaining unit is used for obtaining the symbol error rate according to the voice information and the convolutional code decoding output bit;
the joint decoding checking unit is used for performing joint decoding checking according to the CRC checking result and the symbol error rate;
and the decoding control unit is used for closing the voice information receiving channel when the joint decoding test is passed.
10. The apparatus according to claim 9, wherein the symbol error rate acquisition unit is configured to:
performing convolutional code encoding on the convolutional code decoding output bits to obtain encoded output bits;
obtaining comparison check bits according to the positive and negative states of the voice information;
and comparing the coded output bits with the comparison check bits in sequence, and obtaining the symbol error rate according to the comparison result.
11. The speech information decoding apparatus according to claim 10, wherein the symbol error rate acquisition unit is further configured to:
and marking positive sign information in the voice information as 0 bit, marking negative sign information in the voice information as 1 bit, and obtaining comparison check bits.
12. The speech information decoding apparatus according to claim 10, wherein the symbol error rate acquisition unit is further configured to:
counting the total number M of bits of the coded output bits;
comparing the coded output bits with the comparison check bits in sequence, and counting different bit numbers N;
the ratio N/M of the different number of bits N to the total number of bits M is used as the symbol error rate.
13. The apparatus according to claim 9, wherein the joint decoding verification unit is configured to:
when the result of the CRC check passes and the symbol error rate is lower than a threshold value, the joint decoding check passes; otherwise, the joint coding test fails.
14. The speech information decoding apparatus of claim 13, wherein the threshold is 0.25.
15. The speech information decoding apparatus of claim 9, wherein the convolutional code decoding comprises Viterbi decoding.
16. The speech information decoding apparatus according to claim 9, wherein the decoding control unit is further configured to:
when the joint decoding test fails, continuously receiving the input voice information;
performing joint decoding inspection on the continuously received voice information;
and closing the voice information receiving channel when the joint decoding test passes or the voice information is completely received.
17. A speech information decoding apparatus, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the method of any of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 8.
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