Communication method and device of marine very high frequency equipment, electronic equipment and storage medium

Abstract

The invention discloses a communication method and device for marine very high frequency equipment, electronic equipment and a storage medium. The method comprises the following steps: determining an original voice signal, performing signal processing on the original voice signal, and determining semantic text data; performing data processing on the semantic text data, and determining effective text data in the semantic text data; generating an effective text signal corresponding to the effective text data, and transmitting the effective text signal to a voice receiving end through a target communication channel; and the voice receiving end determines a target communication voice based on the effective text signal. Based on the technical scheme of the invention, the communication quality of the marine very high frequency equipment can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a communication method, device, electronic equipment and storage medium for shipboard very high frequency equipment. Background Art

[0002] Very High Frequency (VHF) equipment on board is an important communication channel between ships and ships, and between ships and land-based stations during navigation. Currently, VHF communication has the problem of poor communication quality due to objective factors such as crew accents, environmental noise, low volume of VHF equipment, and crowded communication channels.

[0003] In the related technology, the transmission voice signal is usually converted into text, and the text data is further transmitted to achieve end-to-end communication. That is, the comprehensibility of communication information is improved based on the readability of the text, and the congestion of the communication channel is reduced based on the low bandwidth characteristics of text transmission to improve the communication quality. However, the improvement effect of communication quality is not obvious and it is difficult to meet the high-quality communication needs of users. Summary of the invention

[0004] The present invention provides a communication method, device, electronic equipment and storage medium for shipboard very high frequency equipment, so as to solve the technical problem that the communication quality of the current shipboard very high frequency equipment is poor.

[0005] According to one aspect of the present invention, there is provided a communication method for a shipboard VHF device, the method comprising:

[0006] Determine an original speech signal, perform signal processing on the original speech signal, and determine semantic text data;

[0007] Performing data processing on the semantic text data to determine valid text data in the semantic text data;

[0008] generating a valid text signal corresponding to the valid text data, and transmitting the valid text signal to a voice receiving end through a target communication channel;

[0009] So that the voice receiving end determines the target communication voice based on the effective text signal.

[0010] According to another aspect of the present invention, there is provided a communication device for a ship-based VHF device, the device comprising:

[0011] A signal processing module, used for determining an original speech signal, performing signal processing on the original speech signal, and determining semantic text data;

[0012] A data processing module, used for performing data processing on the semantic text data to determine valid text data in the semantic text data;

[0013] A signal transmission module, used for generating a valid text signal corresponding to the valid text data, and transmitting the valid text signal to a voice receiving end through a target communication channel;

[0014] The voice receiving module is used to enable the voice receiving end to determine the target communication voice based on the valid text signal.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the communication method of the ship's very high frequency device described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the communication method of a ship-based very high frequency device according to any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention determines the original voice signal, performs signal processing on the original voice signal, and determines the semantic text data; performs data processing on the semantic text data to determine the valid text data in the semantic text data; generates a valid text signal corresponding to the valid text data, and transmits the valid text signal to the voice receiving end through the target communication channel; so that the voice receiving end determines the target communication voice based on the valid text signal. The present invention extracts the valid text data in the semantic text data to perform voice communication, thereby filtering out invalid data in the text data corresponding to the voice signal, and improving the comprehensibility and effectiveness of the voice received by the voice receiving end; the present invention only transmits valid text data, which can avoid the situation where the communication channel resources are limited and multiple voice signals occupy the communication channel at the same time, and the voice signal cannot be stably transmitted. The stability of voice signal transmission is ensured, and the communication quality of shipboard very high frequency equipment is effectively improved.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a system architecture diagram of a ship-based VHF device provided according to an embodiment of the present invention;

[0024] Figure 2 is a flow chart of a communication method of a ship-based VHF device provided according to Embodiment 1 of the present invention;

[0025] Figure 3 is a flow chart of a communication method of a ship-based VHF device provided according to a second embodiment of the present invention;

[0026] Figure 4 is an overall flow chart of data processing provided according to an embodiment of the present invention;

[0027] Figure 5 is an overall flow chart of a communication method for a ship-based VHF device provided according to an embodiment of the present invention;

[0028] Figure 6 2 is a schematic diagram of the structure of a communication device for a ship-based VHF device provided according to a third embodiment of the present invention;

[0029] Figure 7 The invention is a schematic diagram of the structure of an electronic device for implementing the communication method of the ship-based VHF device according to the embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Before describing the embodiments of the present invention, the communication terminal and the ship-based VHF device involved in the communication method of the ship-based VHF device are described: the communication terminal may include a voice transmitting terminal and a voice receiving terminal, wherein the voice transmitting terminal may be a ship terminal or a land terminal, and the voice receiving terminal may be a ship terminal or a land terminal. The communication terminal may be equipped with a ship-based VHF device, such as Figure 1 As shown, Figure 1 1 is a system architecture diagram of a ship VHF device provided according to an embodiment of the present invention. The ship VHF device may include a transmitter for transmitting voice signals, a receiver for receiving voice signals, a display, a speaker, a microphone, a control unit, an intelligent analysis unit, and a panel unit. The following embodiment is specifically described with the voice sending end as the execution subject.

[0033] Embodiment 1

[0034] Figure 2 A flow chart of a communication method for a ship VHF device is provided for the first embodiment of the present invention. This embodiment is applicable to the case where a ship VHF device is used for communication by voice processing. The method can be executed by a communication device for a ship VHF device. The communication device for a ship VHF device can be implemented in the form of hardware and / or software. The communication device for a ship VHF device can be configured in a computer. Figure 2 As shown, the method includes:

[0035] S110: Determine an original speech signal, perform signal processing on the original speech signal, and determine semantic text data.

[0036] The original voice signal may be understood as an unprocessed voice signal. In the embodiment of the present invention, the original voice signal may include environmental noise or invalid voice, etc. The invalid voice may be redundant voice or non-standard terminology voice, etc.

[0037] The semantic text data may be understood as text data related to the original speech signal. Optionally, the semantic text data may represent the specific semantics of the original speech signal.

[0038] S120: Perform data processing on the semantic text data to determine valid text data in the semantic text data.

[0039] The valid text data may be understood as valid text data in the semantic text data. Optionally, the valid text data may be determined by performing intent recognition and key data extraction on the semantic text data through a language model.

[0040] Optionally, the performing data processing on the semantic text data to determine valid text data in the semantic text data includes:

[0041] Performing intent recognition on the semantic text data through a natural language model to determine at least one target semantic intent;

[0042] For each of the target semantic intents, determining sub-text data corresponding to the target semantic intent, and extracting data from the sub-text data using a language representation model to obtain key text data;

[0043] Valid text data in the semantic text data is determined according to the target semantic intent and the key text data.

[0044] The natural language model can be understood as a machine learning model with a semantic intent recognition function. In the embodiment of the present invention, the natural language model can be preset according to the scene requirements, and is not specifically limited here.

[0045] The target semantic intent may understand the semantic intent represented by the semantic text data. Optionally, the target semantic intent may include navigation safety, port terminal operation, emergency rescue, navigation coordination, information exchange, ship management or training exercises, etc.

[0046] The subtext data may be understood as a text data segment in the semantic text data that is related to the target semantic intent. In the embodiment of the present invention, the subtext data corresponding to different target semantic intents may be different.

[0047] The language representation model can be understood as a machine learning model with a key data extraction function. In an embodiment of the present invention, the language representation model can be preset according to the scenario requirements, and is not specifically limited here. Optionally, the language representation model can be a Bert model.

[0048] The key text data may be understood as key text data in the subtext data. Optionally, the key text data may include at least one of a receiving end identifier, location-related data, time-related data, and event description data.

[0049] Optionally, determining the valid text data in the semantic text data according to the target semantic intent and the key text data includes:

[0050] For each of the sub-text data, when the key text data is not empty and the key text data matches the target semantic intent, encoding the target semantic intent and the key text data to obtain valid sub-data;

[0051] Valid text data in the semantic text data is determined according to at least one of the valid sub-data.

[0052] Exemplarily, for the sub-text data of the target, the target semantic intent is navigation safety, and the event description data of the key text data is training description data, then the key text data does not match the target semantic intent.

[0053] In the embodiment of the present invention, the specific manner of encoding the target semantic intent and the key text data is not specifically limited. Optionally, the encoding operation can be used to improve data transmission security.

[0054] The useful sub-data may be understood as useful data segments that can be communicated and transmitted.

[0055] S130: Generate a valid text signal corresponding to the valid text data, and transmit the valid text signal to a voice receiving end through a target communication channel.

[0056] The valid text signal may be understood as a communication signal related to the valid text data. The target communication channel may be a communication channel related to a shipboard VHF device.

[0057] The voice receiving end may be determined based on the valid text signal, that is, the valid text signal includes relevant communication information of the voice receiving end.

[0058] S140, enabling the voice receiving end to determine a target communication voice based on the valid text signal.

[0059] The target communication voice may be related to the valid text data.

[0060] The technical solution of the embodiment of the present invention determines the original voice signal, performs signal processing on the original voice signal, and determines the semantic text data; performs data processing on the semantic text data to determine the valid text data in the semantic text data; generates a valid text signal corresponding to the valid text data, and transmits the valid text signal to the voice receiving end through the target communication channel; so that the voice receiving end determines the target communication voice based on the valid text signal. The present invention extracts the valid text data in the semantic text data to perform voice communication, thereby filtering out invalid data in the text data corresponding to the voice signal, and improving the comprehensibility and effectiveness of the voice received by the voice receiving end; the present invention only transmits valid text data, which can avoid the situation where the communication channel resources are limited and multiple voice signals occupy the communication channel at the same time, and the voice signal cannot be stably transmitted. The stability of voice signal transmission is ensured, and the communication quality of shipboard very high frequency equipment is effectively improved.

[0061] Embodiment 2

[0062] Figure 3 This is a flow chart of a communication method for a ship-based VHF device provided in Embodiment 2 of the present invention. This embodiment is directed to the above-mentioned embodiment, in which the original voice signal is processed to determine the semantic text data for refinement. Figure 3 As shown, the method includes:

[0063] S210: Determine an original speech signal.

[0064] S220: Perform spectrum denoising on the original speech signal using a Fourier transform algorithm to obtain a denoised first speech signal.

[0065] The Fourier transform algorithm may be a short-time Fourier transform (STFT) algorithm, which can divide the speech signal into short time segments.

[0066] The first speech signal can be understood as a denoised speech signal.

[0067] Optionally, performing spectrum denoising on the original speech signal by using a Fourier transform algorithm to obtain a denoised first speech signal includes:

[0068] Slice the original speech signal using preset signal slicing parameters to obtain a plurality of first signal segments, wherein the signal slicing parameters include frame length and / or frame shift;

[0069] determining at least one noise signal segment among the plurality of first signal segments according to a noise threshold, wherein the noise threshold is determined according to a root mean square energy value of the first signal segment;

[0070] Performing a short-time Fourier transform on at least one of the noise signal segments to determine a noise signal spectrum; and performing a short-time Fourier transform on the original speech signal to obtain a speech signal spectrum;

[0071] A denoised signal spectrum is determined according to the speech signal spectrum and the noise signal spectrum, and a short-time inverse Fourier transform is performed on the denoised signal spectrum to obtain a denoised first speech signal.

[0072] The signal segmentation parameters may be understood as parameters used for voice signal segmentation. For example, the frame length may be 40 ms, and the frame shift may be 20 ms.

[0073] Specifically, the steps of performing spectrum denoising on the original speech signal by using a Fourier transform algorithm to obtain a denoised first speech signal are described in the following manner by formula calculation:

[0074] 1. Select signal segmentation parameters with a frame length of 40 ms and a frame shift of 20 ms to segment the original speech signal to obtain multiple first signal segments with a length N of 40 ms.

[0075] 2. Determine the root mean square energy value of each first signal segment x(t,N), and the implementation formula is as follows:

[0076]

[0077] Wherein, RMS(t,N) represents the root mean square energy value, N represents the frame length, and t represents the frame shift.

[0078] 3. Select the 10th percentile root mean square energy value as the noise threshold, and take the first signal segment whose root mean square energy value is lower than the noise threshold as the noise signal segment.

[0079] 4. Perform short-time Fourier transform on the noise signal fragment through STFT to determine the noise signal spectrum; perform short-time Fourier transform on the original speech signal to obtain the speech signal spectrum. The implementation formula is as follows:

[0080]

[0081] Among them, x(t) represents the input signal (sound signal segment or original speech signal), ω(t) represents the preset Hamming window function, τ represents the time offset, ω represents the angular frequency, and X(τ,ω) represents the output spectrum (noise signal spectrum or speech signal spectrum).

[0082] 5. Calculate the average value N(ω) of the noise signal spectrum, and determine the denoised signal spectrum based on the average value N(ω). The implementation formula (spectral subtraction formula) is as follows:

[0083] Y(τ,ω)=max(|X(τ,ω)|-αN(ω),0)

[0084] Among them, Y(τ,ω) represents the spectral subtraction output (denoised signal spectrum), α represents the spectral subtraction coefficient, N(ω) represents the spectral subtraction input (the average value of the noise signal spectrum), and X(τ,ω) represents the spectral subtraction input (speech signal spectrum). Among them, α can be 1.

[0085] 6. The denoised signal spectrum is inversely transformed by the inverse short-time Fourier transform (ISTFT) algorithm to obtain the first speech signal after denoising. The implementation formula is as follows:

[0086]

[0087] Wherein, x(t) represents the output signal (first speech signal), X(τ, ω) represents the input signal (denoised signal spectrum), ω(t) represents the preset Hamming window function, τ represents the time offset, and ω represents the angular frequency.

[0088] S230: Adjust the volume of the first speech signal using a first gain parameter to obtain a second speech signal after the volume is adjusted.

[0089] The first gain parameter is determined according to a global root mean square energy value corresponding to the first speech signal.

[0090] Optionally, the adjusting the volume of the first speech signal by using a first gain parameter to obtain a second speech signal after the volume is adjusted includes:

[0091] Slice the first speech signal according to a preset signal slice parameter to obtain a plurality of second signal segments;

[0092] For each second signal segment, performing volume analysis on the second signal segment according to the enhancement threshold, and if the second signal segment is a low-volume segment, performing volume enhancement on the second signal segment according to the first gain parameter to obtain an enhanced signal segment;

[0093] The second speech signal after volume adjustment is determined based on the enhanced signal segment.

[0094] Optionally, the determining the second speech signal after the volume is adjusted based on the enhanced signal segment includes:

[0095] When the root mean square energy values of multiple second signal segments meet the volume compression condition, at least one high-volume segment with a root mean square energy value exceeding the compression threshold among the multiple second segmented signals is subjected to volume compression according to a second gain parameter to obtain a compressed signal segment, where the second gain parameter is determined according to the maximum and minimum values among the root mean square energy values of the multiple second signal segments;

[0096] Determine a signal to be compensated according to the compressed signal segment;

[0097] Determine a target gain parameter according to the first gain parameter and the second gain parameter, and perform gain compensation on the signal to be compensated according to the target gain parameter to obtain the second voice signal with adjusted volume.

[0098] Specifically, the following steps for adjusting the volume of the first voice signal by the first gain parameter to obtain the second voice signal with adjusted volume are described in a formula calculation manner:

[0099] 1. Select signal segmentation parameters with a frame length of 40 ms and a frame shift of 20 ms to segment the first voice signal to obtain multiple second signal segments.

[0100] 2. Determine the root mean square energy value RMS(t,N) of each second signal segment, set a fixed energy value threshold, that is, an enhancement threshold T1, and screen the second signal segments with RMS(t,N) < T1 as low-volume segments.

[0101] 3. For each low-volume segment, calculate the global root mean square energy value RMS g , determine the intermediate value RMS g according to RMS t , and determine the implementation formula of the first gain parameter according to RMS t as follows:

[0102]

[0103] Among them, RMS t represents the intermediate value, and RMS g represents the global root mean square energy value.

[0104] θ = RMS t / RMS(t,N)

[0105] Among them, θ represents the first gain parameter, RMS t represents the intermediate value, and RMS(t,N) represents the root mean square energy value of the second signal segment.

[0106] 4. Apply the first gain factor to the corresponding low-volume segment to obtain an enhanced signal segment of the low-volume segment.

[0107] 5. Determine the maximum and minimum RMS values ​​in RMS(t,N), that is, RMS max and RMS min , if RMS max -RMS min >ΔRMS, the volume compression condition is met, that is, the volume compression operation is required, where ΔRMS is the preset threshold.

[0108] 6. Calculate the mean μ and standard deviation σ of each segment RMS(t,N), determine the dynamic energy value threshold, that is, the compression threshold T2, and select the second signal segment with RMS(t,N)>T2 as the high-volume segment. The implementation is shown as follows:

[0109] T2=μ+kσ

[0110] Wherein, T2 represents the compression threshold, μ represents the mean of RMS(t,N), σ represents the standard deviation of RMS(t,N), and k represents a preset constant value.

[0111] Alternatively, the 75th percentile root mean square energy value of the root mean square energy value of each second signal segment in the sequence is taken as the compression threshold RMS thresh , that is, when the amplitude of the second signal segment exceeds the compression threshold, volume compression is performed, and the implementation formula is as follows:

[0112]

[0113] Among them, RMS thresh represents the compression threshold, RMS(t,N) represents the root mean square energy value, cr represents the second gain parameter, and g(t,N) represents the compressed signal segment.

[0114] 7. Set the basic compression ratio r according to the scene requirements b and the maximum compression ratio r m , according to r b and r m Calculate the target compression ratio cr, use cr as the second gain parameter, and implement the formula as follows:

[0115]

[0116] Among them, cr represents the target compression ratio, r b Represents the basic compression ratio, r m Indicates the maximum compression ratio, RMS max represents the maximum value of the root mean square energy value of the second signal segment, RMS min represents the minimum value among the RMS energy values ​​of the second signal segment.

[0117] 8. Determine a target gain parameter, and perform gain compensation on the signal to be compensated according to the target gain parameter. The implementation formula is as follows:

[0118]

[0119] Wherein, g represents the target gain parameter, x(t) represents the output signal (the second speech signal), and x(t) represents the signal to be compensated. Wherein, g may be the average value of the first gain parameter and the second gain parameter.

[0120] S240: Perform semantic recognition on the first voice signal through a voice recognition model to determine the semantic text data corresponding to the second voice signal.

[0121] The speech recognition model (Automatic Speech Recognition, ASR) may have the function of recognizing semantic text corresponding to a speech signal.

[0122] Specifically, before applying the speech recognition model for semantic recognition, the model is quantized to quantize the original model into an 8-bit model to reduce the consumption of hardware resources for terminal deployment; the model is exported to an open file format (OpenNeural Network Exchange, ONNX) and loaded into the embedded computing function module.

[0123] S250: Perform data processing on the semantic text data to determine valid text data in the semantic text data.

[0124] Figure 4 1 is an overall flow chart of data processing provided according to an embodiment of the present invention. Figure 4 As shown, the overall process of data processing can be:

[0125] Specifically, 1. Perform intent recognition on the semantic text data output by ASR. The identified target semantic intent can be shown in the following Table 1:

[0126] Table 1

[0127]

[0128] 2. Extract key data of semantic text data through Bert model. The extracted key text data can be shown in Table 2 below:

[0129] Table 2

[0130]

[0131] 3. If the extracted key text data is empty, or the key text data does not match the target semantic intent, the identified related text data (sub-text data) is considered invalid data and can be directly blocked and filtered to obtain valid text data.

[0132] S260: Generate a valid text signal corresponding to the valid text data, and transmit the valid text signal to a voice receiving end through a target communication channel.

[0133] S270, enabling the voice receiving end to determine the target communication voice based on the valid text signal.

[0134] Specifically, for the voice receiving end, the received valid text signal is decoded, and the valid text signal is converted into voice offline through a text-to-speech (TTS) model to obtain the target communication voice.

[0135] The technical solution of the embodiment of the present invention performs spectrum denoising on the original voice signal through a Fourier transform algorithm to obtain a denoised first voice signal; adjusts the volume of the first voice signal through a first gain parameter to obtain a volume-adjusted second voice signal, wherein the first gain parameter is determined according to the global root mean square energy value corresponding to the first voice signal; performs semantic recognition on the first voice signal through a voice recognition model to determine the semantic text data corresponding to the second voice signal. The present invention achieves high-quality voice signal denoising and high-accuracy semantic recognition.

[0136] Optionally, Figure 5 FIG. 1 is an overall flow chart of a communication method for a ship-based VHF device provided according to an embodiment of the present invention. Figure 5 As shown, the overall process of the communication method of the ship-borne very high frequency equipment may include: 1. spectral denoising implemented by a denoising module (determining the first voice signal corresponding to the original voice signal); 2. volume adjustment implemented by a voice enhancement module (determining the second voice signal corresponding to the first voice signal); 3. semantic recognition implemented by a voice recognition module (determining the semantic text data corresponding to the second voice signal); 4. effective text extraction implemented by a voice understanding module (determining the effective text data corresponding to the semantic text data); 5. signal-to-speech conversion implemented by a voice generation module (determining the target communication voice corresponding to the effective text signal).

[0137] Based on the technical solution of this embodiment, 1. The communication quality and efficiency of VHF equipment are improved. The denoising module and the voice enhancement module can ensure that the communication data is clearer and purer. Wireless transmission can increase the data transmission speed. The voice generation module can ensure the standardization and comprehensibility of voice output. 2. Invalid information is shielded. The semantic understanding module can effectively filter invalid information and release the communication pressure of the VHF channel. 3. Convenience of implementation. An intelligent analysis module is added to the traditional VHF communication equipment without changing the user's operation. The high-quality VHF communication effect and efficiency can enhance the user experience. 4. Improve safety and reliability. It can improve the communication quality of VHF and thus ensure the safety of ship navigation.

[0138] Embodiment 3

[0139] Figure 6 This is a schematic diagram of the structure of a communication device for a ship-based VHF device provided in Embodiment 3 of the present invention. Figure 6 As shown, the device includes: a signal processing module 310 , a data processing module 320 , a signal transmission module 330 and a voice receiving module 340 .

[0140] Among them, the signal processing module 310 is used to determine the original voice signal, perform signal processing on the original voice signal, and determine the semantic text data; the data processing module 320 is used to perform data processing on the semantic text data and determine the valid text data in the semantic text data; the signal transmission module 330 is used to generate a valid text signal corresponding to the valid text data, and transmit the valid text signal to the voice receiving end through the target communication channel; the voice receiving module 340 is used to enable the voice receiving end to determine the target communication voice based on the valid text signal.

[0141] The technical solution of the embodiment of the present invention determines the original voice signal, performs signal processing on the original voice signal, and determines the semantic text data; performs data processing on the semantic text data to determine the valid text data in the semantic text data; generates a valid text signal corresponding to the valid text data, and transmits the valid text signal to the voice receiving end through the target communication channel; so that the voice receiving end determines the target communication voice based on the valid text signal. The present invention extracts the valid text data in the semantic text data to perform voice communication, thereby filtering out invalid data in the text data corresponding to the voice signal, and improving the comprehensibility and effectiveness of the voice received by the voice receiving end; the present invention only transmits valid text data, which can avoid the situation where the communication channel resources are limited and multiple voice signals occupy the communication channel at the same time, and the voice signal cannot be stably transmitted. The stability of voice signal transmission is ensured, and the communication quality of shipboard very high frequency equipment is effectively improved.

[0142] Optionally, the signal processing module 310 includes: a spectrum denoising unit, a volume adjustment unit and a semantic recognition unit;

[0143] The spectrum denoising unit is used to perform spectrum denoising on the original speech signal by using a Fourier transform algorithm to obtain a denoised first speech signal;

[0144] The volume adjustment unit is used to adjust the volume of the first speech signal by using a first gain parameter to obtain a second speech signal after the volume is adjusted, wherein the first gain parameter is determined according to a global root mean square energy value corresponding to the first speech signal;

[0145] The semantic recognition unit is used to perform semantic recognition on the first voice signal through a voice recognition model to determine the semantic text data corresponding to the second voice signal.

[0146] Optionally, the spectrum denoising unit is specifically used to:

[0147] Slice the original speech signal using preset signal slicing parameters to obtain a plurality of first signal segments, wherein the signal slicing parameters include frame length and / or frame shift;

[0148] determining at least one noise signal segment among the plurality of first signal segments according to a noise threshold, wherein the noise threshold is determined according to a root mean square energy value of the first signal segment;

[0149] Performing a short-time Fourier transform on at least one of the noise signal segments to determine a noise signal spectrum; and performing a short-time Fourier transform on the original speech signal to obtain a speech signal spectrum;

[0150] A denoised signal spectrum is determined according to the speech signal spectrum and the noise signal spectrum, and a short-time inverse Fourier transform is performed on the denoised signal spectrum to obtain a denoised first speech signal.

[0151] Optionally, the volume adjustment unit includes: a slice processing subunit, a volume analysis subunit and a signal determination subunit;

[0152] The fragmentation processing subunit is used to perform fragmentation processing on the first speech signal according to a preset signal fragmentation parameter to obtain a plurality of second signal fragments;

[0153] The volume analysis subunit is configured to perform volume analysis on each second signal segment according to an enhancement threshold, and if the second signal segment is a low-volume segment, perform volume enhancement on the second signal segment according to a first gain parameter to obtain an enhanced signal segment;

[0154] The signal determination subunit is used to determine the second speech signal after volume adjustment based on the enhanced signal segment.

[0155] Optionally, the signal determination subunit is specifically used to:

[0156] When the root mean square energy values ​​of the plurality of second signal segments meet the volume compression condition, volume compression is performed on at least one high volume segment whose root mean square energy value in the plurality of second fragmented signals exceeds a compression threshold according to a second gain parameter to obtain a compressed signal segment, wherein the second gain parameter is determined according to a maximum value among the root mean square energy values ​​of the plurality of second signal segments;

[0157] Determining a signal to be compensated according to the compressed signal segment;

[0158] A target gain parameter is determined according to the first gain parameter and the second gain parameter, and gain compensation is performed on the signal to be compensated according to the target gain parameter to obtain the second speech signal after volume adjustment.

[0159] Optionally, the signal transmission module 330 includes: an intention recognition unit, a data extraction unit, and a valid text determination unit;

[0160] The intention recognition unit is used to perform intention recognition on the semantic text data through a natural language model to determine at least one target semantic intention;

[0161] The data extraction unit is used to determine, for each of the target semantic intents, the sub-text data corresponding to the target semantic intent, and extract the sub-text data through a language representation model to obtain key text data;

[0162] The valid text determination unit is used to determine the valid text data in the semantic text data according to the target semantic intent and the key text data.

[0163] Optionally, the valid text determination unit is specifically used to:

[0164] For each of the sub-text data, when the key text data is not empty and the key text data matches the target semantic intent, encoding the target semantic intent and the key text data to obtain valid sub-data;

[0165] Valid text data in the semantic text data is determined according to at least one of the valid sub-data.

[0166] The communication device for ship VHF equipment provided in the embodiment of the present invention can execute the communication method for ship VHF equipment provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0167] Embodiment 4

[0168] Figure 7 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0169] like Figure 7 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0170] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0171] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the communication method of the ship's VHF equipment.

[0172] In some embodiments, the communication method of the ship VHF device can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the communication method of the ship VHF device described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the communication method of the ship VHF device by any other appropriate means (for example, by means of firmware).

[0173] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0174] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0175] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0176] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0177] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0178] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0179] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0180] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A communication method for a shipborne VHF device, characterized in that: include: Determine an original speech signal, perform signal processing on the original speech signal, and determine semantic text data; Performing data processing on the semantic text data to determine valid text data in the semantic text data; generating a valid text signal corresponding to the valid text data, and transmitting the valid text signal to a voice receiving end through a target communication channel; So that the voice receiving end determines the target communication voice based on the effective text signal.

2. The method according to claim 1, characterized in that: The performing signal processing on the original speech signal to determine semantic text data includes: Performing spectrum denoising on the original speech signal by using a Fourier transform algorithm to obtain a denoised first speech signal; Adjusting the volume of the first speech signal by a first gain parameter to obtain a second speech signal after the volume is adjusted, wherein the first gain parameter is determined according to a global root mean square energy value corresponding to the first speech signal; The first speech signal is semantically recognized through a speech recognition model to determine the semantic text data corresponding to the second speech signal.

3. The method according to claim 2, characterized in that The method of performing spectrum denoising on the original speech signal by using a Fourier transform algorithm to obtain a denoised first speech signal includes: Slice the original speech signal using preset signal slicing parameters to obtain a plurality of first signal segments, wherein the signal slicing parameters include frame length and / or frame shift; determining at least one noise signal segment among the plurality of first signal segments according to a noise threshold, wherein the noise threshold is determined according to a root mean square energy value of the first signal segment; Performing a short-time Fourier transform on at least one of the noise signal segments to determine a noise signal spectrum; and performing a short-time Fourier transform on the original speech signal to obtain a speech signal spectrum; A denoised signal spectrum is determined according to the speech signal spectrum and the noise signal spectrum, and a short-time inverse Fourier transform is performed on the denoised signal spectrum to obtain a denoised first speech signal.

4. The method according to claim 2, characterized in that: The step of adjusting the volume of the first speech signal by using a first gain parameter to obtain a second speech signal after the volume is adjusted includes: Slice the first speech signal according to a preset signal slice parameter to obtain a plurality of second signal segments; For each second signal segment, performing volume analysis on the second signal segment according to the enhancement threshold, and if the second signal segment is a low-volume segment, performing volume enhancement on the second signal segment according to the first gain parameter to obtain an enhanced signal segment; The second speech signal after volume adjustment is determined based on the enhanced signal segment.

5. The method according to claim 4, characterized in that The step of determining the second speech signal after the volume is adjusted based on the enhanced signal segment includes: When the root mean square energy values ​​of the plurality of second signal segments meet the volume compression condition, volume compression is performed on at least one high volume segment whose root mean square energy value in the plurality of second fragmented signals exceeds a compression threshold according to a second gain parameter to obtain a compressed signal segment, wherein the second gain parameter is determined according to a maximum value among the root mean square energy values ​​of the plurality of second signal segments; Determining a signal to be compensated according to the compressed signal segment; A target gain parameter is determined according to the first gain parameter and the second gain parameter, and gain compensation is performed on the signal to be compensated according to the target gain parameter to obtain the second speech signal after volume adjustment.

6. The method according to claim 1, characterized in that The performing data processing on the semantic text data to determine valid text data in the semantic text data includes: Performing intent recognition on the semantic text data through a natural language model to determine at least one target semantic intent; For each of the target semantic intents, determining subtext data corresponding to the target semantic intent, and extracting data from the subtext data using a language representation model to obtain key text data; Valid text data in the semantic text data is determined according to the target semantic intent and the key text data.

7. The method according to claim 6, characterized in that The determining the valid text data in the semantic text data according to the target semantic intent and the key text data includes: For each of the sub-text data, when the key text data is not empty and the key text data matches the target semantic intent, encoding the target semantic intent and the key text data to obtain valid sub-data; Valid text data in the semantic text data is determined according to at least one of the valid sub-data.

8. A communication device for a ship's VHF equipment, characterized in that: include: A signal processing module, used for determining an original speech signal, performing signal processing on the original speech signal, and determining semantic text data; A data processing module, used for performing data processing on the semantic text data to determine valid text data in the semantic text data; A signal transmission module, used for generating a valid text signal corresponding to the valid text data, and transmitting the valid text signal to a voice receiving end through a target communication channel; The voice receiving module is used to enable the voice receiving end to determine the target communication voice based on the valid text signal.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the communication method of the ship-based VHF device according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the communication method of a shipborne very high frequency device according to any one of claims 1 to 7 when the processor executes the computer instructions.

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