Intelligent codec management system and method based on multi-mode codec

Abstract

The multi-mode codec-based voice intelligent codec management system and method of the present application, the system comprises a codec library module for storing multiple standard voice codecs and generating a codec available signal; a state monitoring module for collecting network parameter signals and device capability signals in real time and generating an environment state signal; a service rule module for storing a private network service policy and generating a service policy signal, wherein the private network service policy defines codec priorities based on video conference, enterprise directory and OA integration requirements; an intelligent selection module for receiving the codec available signal, the environment state signal and the service policy signal, performing multi-dimensional weighted calculation through an intelligent algorithm to generate a codec selection signal; and a management interface module for receiving the codec selection signal and the environment state signal, generating a codec configuration signal and a monitoring display signal. The present application can solve the problem of rigid voice codec scheme in industry private networks, which is difficult to dynamically adapt to complex network environments.

Description

Technical Field

[0001] This invention relates to the field of communication network technology, and more specifically to a voice intelligent codec management system and method based on multi-standard codecs. Background Technology

[0002] As the core network architecture, the IP Multimedia Subsystem (IMS) provides a unified control and management platform for various communication services. In the public network domain, IMS technology is already very mature, capable of providing stable and rich voice, video, and other multimedia services. However, when applying IMS technology to private networks in industries such as energy, power, and coal mining, its inherent design and deployment models face a series of severe challenges. Traditional IMS systems are typically designed for large-scale, high-bandwidth, and statically stable network environments used by operators, requiring high hardware resources and complex network structures. This directly leads to high deployment costs and long deployment cycles in private network scenarios. Furthermore, private network environments have unique characteristics, such as potentially limited and fluctuating network bandwidth, diverse terminal device types with varying processing capabilities, and more customized business requirements, such as the need to integrate specific functions like video conferencing, enterprise address books, and office automation.

[0003] In existing technologies, the selection and management mechanisms for voice codecs are relatively simple and fixed. Typically, the system selects a codec at the beginning of a session based on limited static configuration or simple rules, and continues to use that codec throughout the communication session. This rigid management approach cannot adapt to the dynamically changing network conditions of private networks. For example, when network bandwidth suddenly drops, the system may not be able to automatically switch to a codec with a higher compression ratio and better packet loss resistance, leading to a severe decline in voice quality or even call interruption; conversely, when network conditions are good, the system may still be using a low-quality codec, resulting in a waste of bandwidth resources. Although the concept of lightweight IMS has emerged in the industry, aiming to reduce deployment costs and resource consumption and enhance adaptability to private network services through technologies such as containerization and microservices, these improvements are mostly focused on the network architecture and service provision levels. In the critical aspect of voice codec management, a dynamic mechanism that can deeply perceive the network, device, and service context and make real-time, intelligent decisions is still lacking. Therefore, industry private networks urgently need a comprehensive solution that can inherit the advantages of lightweight IMS in terms of deployment, cost and flexibility, and solve the problem of intelligent codec management, so as to achieve the optimal balance between voice service quality and network resource utilization efficiency. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this invention is to provide a voice intelligent codec management system and method based on multi-standard codecs, to solve the problem of rigid voice codec schemes in industry private networks that are difficult to dynamically adapt to complex network environments. This invention solves the above problems by constructing a system that integrates a multi-standard codec library, status monitoring, service rules, intelligent selection, and management interfaces. The system first uses a status monitoring module to perceive the network and device status in real time, while a service rules module provides private network service policies; the intelligent selection module integrates this information and uses intelligent algorithms to dynamically select the optimal codec from the codec library; the management interface module performs configuration and provides a visual maintenance interface. This method achieves real-time and dynamic matching of codecs with network conditions, device capabilities, and service scenarios, thereby significantly improving the system's adaptability and resource utilization efficiency while ensuring voice quality.

[0005] This invention provides a voice intelligent codec management system based on multi-standard codecs, comprising:

[0006] The codec library module stores various standard speech codecs and generates usable codec signals.

[0007] The status monitoring module collects network parameter signals and device capability signals in real time and generates environmental status signals.

[0008] The business rules module stores private network business policies and generates business policy signals. The private network business policies define codec priorities based on video conferencing, enterprise address book and OA integration requirements.

[0009] The intelligent selection module receives codec availability signals, environmental status signals, and service policy signals. It generates codec selection signals by performing multi-dimensional weighted calculations using intelligent algorithms. The intelligent algorithms dynamically optimize the selection based on network conditions, device capabilities, and service requirements.

[0010] The management interface module receives codec selection signals and environmental status signals, and generates codec configuration signals and monitoring display signals. The codec configuration signals are used to configure and apply the selected codec in the voice session, and the monitoring display signals are used to display codec performance statistics and operation interface in real time in the management portal.

[0011] In one embodiment of the present invention, the status monitoring module generates an environmental status signal and transmits it to the intelligent selection module and the management interface module; the codec library module generates a codec availability signal and transmits it to the intelligent selection module; the business rules module generates a business policy signal and transmits it to the intelligent selection module; the intelligent selection module generates a codec selection signal and transmits it to the management interface module; the management interface module generates a codec configuration signal and transmits it to the IMS core network to perform codec switching; and simultaneously generates a monitoring display signal and transmits it to the management portal to achieve visual maintenance.

[0012] In one embodiment of the present invention, the codec library module further includes a containerized deployment unit. The containerized deployment unit encapsulates various standard voice codecs into independent container instances, dynamically adjusts the number of container instances according to the system load, and forms a codec resource scheduling signal that is transmitted to the management interface module. When an increase in voice traffic is detected, the container instances are automatically expanded, and when the traffic decreases, the excess container instances are automatically released, realizing elastic allocation of codec resources. At the same time, it supports hybrid deployment on private cloud platforms, public cloud platforms, and general servers. The containerized deployment unit also maintains codec lifecycle management signals, including the start, stop, and health status monitoring of codec instances, to ensure the continuous availability of codec services.

[0013] In one embodiment of the present invention, the status monitoring module further includes a high-reliability monitoring unit. The high-reliability monitoring unit monitors the server hardware resource status, network element operation status, and site connection status in real time, forming a three-level reliability monitoring signal that is transmitted to the intelligent selection module. When any level of fault is detected, a codec switching preparation signal is triggered. The high-reliability monitoring unit continuously collects network quality indicators, including bandwidth fluctuation trends, latency change patterns, and packet loss rate statistics, forming a network quality prediction signal, which is then merged with the environmental status signal and transmitted to the intelligent selection module. The high-reliability monitoring unit also establishes a fault self-healing mechanism, automatically activating a backup codec instance when a codec anomaly is detected.

[0014] In one embodiment of the present invention, the business rules module further includes a private network business adaptation unit. The private network business adaptation unit dynamically adjusts the business strategy signal according to the private network application scenario. For video conferencing services, it prioritizes low-latency codecs; for enterprise address book integration services, it prioritizes high-compatibility codecs; and for office automation integration services, it prioritizes high-compression-rate codecs. The private network business adaptation unit also stores private network-specific business characteristic configurations, including softphone service preference settings and electronic fax service requirement parameters, forming a private network characteristic adaptation signal and merging it into the business strategy signal for transmission to the intelligent selection module.

[0015] In one embodiment of the present invention, the intelligent selection module further includes a multi-dimensional decision-making unit. The multi-dimensional decision-making unit uses a weighted evaluation algorithm to process the codec availability signal, environmental status signal, and service policy signal. The weighted evaluation algorithm comprehensively considers four dimensions of factors: real-time network status, equipment support capability, service quality requirements, and system resource load, to generate the optimal codec selection scheme. The multi-dimensional decision-making unit also has dynamic learning capability, continuously optimizing the weighting parameters based on historical selection results to form an algorithm optimization signal for adjusting subsequent decision-making processes. During the session, the multi-dimensional decision-making unit continuously monitors environmental changes and updates the codec selection signal in real time.

[0016] In one embodiment of the present invention, the management interface module further includes a visual maintenance unit. The visual maintenance unit generates graphical monitoring display signals, which display the usage status, performance index statistics and system resource usage of each codec in real time in the management portal. The visual maintenance unit provides a one-click maintenance operation interface, receives administrator instructions to generate codec configuration adjustment signals, supports batch modification of codec priority and business strategy parameters, and also generates operation audit signals to record all management operations and system automatic decision-making processes, forming a traceable maintenance log for subsequent analysis and optimization.

[0017] In one embodiment of the present invention, the containerized deployment unit further includes a resource optimization component. The resource optimization component implements fine-grained management of codec instances based on a microservice architecture, automatically adjusts container resource quotas according to voice service load, and generates a resource allocation optimization signal that is transmitted to the management interface module. The resource optimization component monitors the resource utilization efficiency of container instances, automatically merges instances when the resource utilization is detected to be lower than a threshold, and automatically triggers horizontal scaling when the resource utilization is continuously too high. The resource optimization component also supports canary release and version rollback functions for codec instances.

[0018] In one embodiment of the present invention, the high-reliability monitoring unit further includes a failover component. The failover component establishes a redundant backup mechanism for codec instances. When a failure is detected in the currently used codec instance, it automatically switches to the standby instance and sends a switchover completion signal to the management interface module. The failover component enables cross-server codec instance disaster recovery. When the primary server fails, the codec service is automatically migrated to the standby server. The failover component also provides a manual switching function, allowing administrators to actively trigger codec instance switching operations through the management interface module.

[0019] This invention also includes a voice intelligent codec management method based on multi-standard codecs, comprising:

[0020] S1: Stores multiple standard speech codecs and generates usable signals for the codecs;

[0021] S2: Real-time acquisition of network parameter signals and device capability signals and generation of environmental status signals, where network parameter signals include bandwidth, latency and packet loss rate information, and device capability signals include terminal type and supported codec information;

[0022] S3: Store private network service policies and generate service policy signals, where the private network service policies define codec priorities based on video conferencing, enterprise address book and OA integration requirements.

[0023] S4: Receive codec availability signals, environmental status signals, and service policy signals, and generate codec selection signals through multi-dimensional weighted calculations using intelligent algorithms. The intelligent algorithms dynamically optimize the selection based on network conditions, device capabilities, and service requirements.

[0024] S5: Receives codec selection signal and environment status signal, generates codec configuration signal and monitoring display signal, wherein the codec configuration signal is used to configure and apply the selected codec in the voice session, and the monitoring display signal is used to display codec performance statistics and operation interface in real time in the management portal.

[0025] This invention provides a voice intelligent codec management system and method based on multi-standard codecs. It addresses the aforementioned problems by constructing a system integrating a multi-standard codec library, status monitoring, service rules, intelligent selection, and management interfaces. The system first uses a status monitoring module to perceive network and device status in real time, while a service rules module provides dedicated network service policies. The intelligent selection module integrates this information and uses intelligent algorithms to dynamically select the optimal codec from the codec library. The management interface module performs configuration and provides a visual maintenance interface. This method achieves real-time and dynamic matching of codecs with network conditions, device capabilities, and service scenarios, thereby significantly improving the system's adaptability and resource utilization efficiency while ensuring voice quality. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a system architecture diagram of a voice intelligent codec management system based on multiple codec standards.

[0028] Figure 2 This is a flowchart of a speech intelligent codec management method based on multiple codec standards. Detailed Implementation

[0029] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0030] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0031] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0032] Please see Figure 1-2 The image shows a voice intelligent codec management system and method based on multi-standard codecs according to the present invention. The voice intelligent codec management system based on multi-standard codecs of the present invention includes: a codec library module, which stores multiple standard voice codecs and generates available codec signals; a status monitoring module, which collects network parameter signals and device capability signals in real time and generates environmental status signals; a business rules module, which stores private network business policies and generates business policy signals, wherein the private network business policies define codec priorities based on video conferencing, enterprise address book, and OA integration requirements; an intelligent selection module, which receives available codec signals, environmental status signals, and business policy signals, and generates codec selection signals through multi-dimensional weighted calculations using intelligent algorithms, wherein the intelligent algorithms dynamically optimize selection based on network conditions, device capabilities, and business requirements; and a management interface module, which receives codec selection signals and environmental status signals, and generates codec configuration signals and monitoring display signals, wherein the codec configuration signals are used to configure and apply the selected codecs in voice conversations, and the monitoring display signals are used to display codec performance statistics and operation interfaces in real time in the management portal.

[0033] like Figure 1As shown, its core structure consists of five interconnected functional modules tightly coupled through specific signal flows. Together, they construct an intelligent voice processing hub capable of dynamically adapting to the complex environment of a private network. This system is deeply integrated into a lightweight IP multimedia subsystem architecture, aiming to solve the problems of unstable voice quality and low resource efficiency caused by the rigidity of traditional codec management. First, the cornerstone of the system is the codec library module. This module is not a simple static storage pool, but a standardized, dynamic resource pool with efficient scheduling capabilities. It integrates a wide variety of voice codecs, all adhering to international or industry standards, ensuring broad compatibility with devices from different manufacturers. This directly inherits the standardized advantage of the product's successful integration with multiple manufacturers, as described in the disclosure document. The core function of this module is to register, manage, and maintain the status of all available codecs, thereby generating a global codec availability signal. This signal is crucial; it is not merely a static list but also contains real-time status information for each codec, such as whether it has been successfully loaded, whether it is currently in a callable state, and its basic characteristic parameters (such as theoretical bandwidth requirements, algorithm complexity, and packet loss resistance). This signal provides the most basic data options for subsequent intelligent decision-making and is a prerequisite for the flexible operation of the entire system. The system's "sensory nerves" are the status monitoring module. This module undertakes the important task of real-time data acquisition, and its monitoring scope covers multiple key dimensions affecting voice quality. On the one hand, it continuously captures fine network parameter signals from the network layer. These parameters include, but are not limited to, real-time available bandwidth, end-to-end transmission latency, packet loss rate, and jitter. These data directly reflect the health status of the current network transmission path. On the other hand, it simultaneously collects device capability signals, which involves identifying the capabilities of terminal devices that initiate or receive voice calls, such as determining whether the terminal is a mobile handheld device, a fixed desktop phone, or a softphone client, and accurately identifying which types of codecs the terminal specifically supports. The status monitoring module filters, aggregates, and performs preliminary fusion processing on these two categories of raw data, ultimately generating a comprehensive environmental status signal. This signal is a dynamic and quantitative description of the current communication environment, providing real and timely contextual basis for intelligent decision-making.

[0034] Furthermore, the system's "strategy brain" is the business rules module. In a private network environment, different business scenarios have vastly different requirements for voice codecs. The role of this module is to transform these diverse and potential business needs into explicit and executable policy instructions. The module internally stores business policies tailored to the private network scenario. These policies clearly define the priority criteria for codec selection under specific business types. For example, when the business involves video conferencing with high real-time requirements, the policy will tend to prioritize low-latency codecs to ensure audio-visual synchronization; when the business involves integration with enterprise address books or office automation systems, the policy may place greater emphasis on the general compatibility of codecs and signaling interaction efficiency. The business rules module generates corresponding business policy signals based on the currently active business type or the administrator's preset global policies. These signals are essentially a set of weighted selection rules that directly guide and constrain the subsequent intelligent selection process. The system's "decision center" is the intelligent selection module. This is the core of the entire system's intelligence; it receives input signals from the aforementioned three modules: the codec availability signal provides "what options are available," the environment status signal provides "what is the current environment like," and the business policy signal provides "what the business needs." The intelligent selection module's embedded intelligent algorithm (which can be a rule-based engine or incorporate more complex machine learning models) performs multi-factor weighted calculations and comprehensive analysis on information from these three dimensions. Within milliseconds, it evaluates and selects the optimal solution from all available codecs that best meets business needs while maintaining resource efficiency in the current environment. For example, when network bandwidth is sufficient and the equipment supports it, it may choose a highly complex codec to provide superior sound quality; once bandwidth constraints are detected, it immediately and dynamically switches to a high-compression codec to ensure call continuity. Its final output codec selection signal is a clear and executable instruction.

[0035] Specifically, the system's "Execution and Interaction Interface" is the management interface module. This module plays a crucial role in bridging the gap between the upper and lower layers. It receives codec selection signals from the intelligent selection module and transforms them into codec configuration signals that the IMS core network and terminal devices can recognize and execute, thereby driving the establishment, negotiation, and seamless switching of codecs during voice conversations. Simultaneously, it receives environmental status signals from the status monitoring module and combines them with the system's own operational status information to generate rich monitoring display signals. These signals are sent to a dedicated management portal, providing operations and maintenance personnel with a real-time view of the entire codec system's operation in a visual graphical interface. This includes the utilization rate of each codec, network quality trends, system resource load, etc., greatly improving the system's observability and maintainability, which aligns perfectly with the one-stop network management and easy-to-maintain goals emphasized in the handover document. In summary, these five modules are interconnected through a tight signal flow to form a closed-loop intelligent management system: the environmental status signal generated by the status monitoring module is transmitted in parallel to the intelligent selection module and the management interface module; the codec library module generates a codec availability signal, which is transmitted to the intelligent selection module; the business rule module generates a business strategy signal, which is transmitted to the intelligent selection module; the intelligent selection module integrates all information to generate a codec selection signal, which is transmitted to the management interface module; finally, the management interface module puts the instructions into practice (codec configuration signal) and makes the status transparent (monitoring display signal). This design achieves fully automated management of the entire process, from environmental perception and intelligent decision-making to precise execution and end-to-end visualization.

[0036] In one embodiment of the present invention, a crucial enhancement was made to the most fundamental codec library module by introducing a containerized deployment unit. This improvement is not merely a change in implementation, but fundamentally enhances the system's core competitiveness in terms of resource utilization efficiency, elastic scalability, and deployment flexibility. It is a core technical means to achieve the "lightweight" and "flexible deployment" goals outlined in the disclosure document. The core idea of ​​the containerized deployment unit is to transform each standard speech codec from its traditional, tightly coupled software library form into independent, lightweight, and portable container instances. For example, the G711 codec, G729 codec, etc., can be encapsulated in separate containers. This encapsulation brings revolutionary advantages. First, it achieves ultimate resource isolation and fine-grained management. Each codec instance runs in its own isolated environment, without interfering with each other, avoiding the risk of the entire speech processing service being dragged down by a single codec malfunction, as is common in traditional methods, significantly improving the overall stability of the system. More importantly, containerization gives the system unprecedented elastic scalability. This unit can continuously monitor the system's speech service processing load, such as the number of concurrent speech sessions and the throughput of audio data packets. Based on these real-time metrics, it dynamically generates codec resource scheduling signals. When it detects peak traffic periods and a sustained increase in load reaching preset thresholds, the unit automatically and quickly expands the corresponding codec container instances—creating new container replicas to share the processing pressure and ensure that voice processing is not delayed or interrupted due to insufficient resources. Conversely, when traffic decreases and is in a low-peak period, the system automatically identifies idle resources and intelligently releases or terminates excess container instances, returning these valuable CPU and memory resources to the server operating system for use by other services. This process achieves "on-demand allocation" of resources, greatly avoiding unnecessary occupation and waste of hardware resources during off-peak hours, perfectly responding to the core requirements of "energy conservation and emission reduction" and "avoiding waste of hardware resources" in the disclosure document.

[0037] like Figure 1As shown, the containerization deployment unit is also responsible for maintaining the entire lifecycle management signals of the codec. This covers the entire process from the startup, operation, and health status monitoring of container instances to graceful shutdown or forced termination. This unit periodically reports the heartbeat and health status of each codec container instance to the management interface module, ensuring that the management layer can monitor the availability of the underlying services in real time. Once a container instance is detected as unresponsive or malfunctioning, the lifecycle management mechanism can attempt to automatically restart the instance or notify the upstream intelligent selection module to temporarily remove the codec from the available list until it recovers its health. This granular lifecycle management lays a solid foundation for the system's high reliability. Finally, due to the platform independence of container technology, this unit enables the entire codec management system to run seamlessly on various heterogeneous infrastructure environments, whether it's a private cloud platform, public cloud services, or physical or virtual general-purpose servers. This achieves the excellent deployment flexibility emphasized in the disclosure document—"deploying to private cloud platforms, public cloud platforms, and general-purpose servers"—completely eliminating dependence on specific proprietary hardware. The high-reliability monitoring unit has an extremely macro and systematic monitoring perspective. It goes beyond simply observing network traffic and latency; instead, it constructs a three-tiered reliability monitoring system, from the underlying hardware to upper-layer applications and cross-site connections. The first tier delves into the server hardware itself, continuously monitoring the status of critical hardware resources, including but not limited to CPU utilization and temperature, memory usage and error rate, hard drive read / write performance and remaining space, and the operational status of network interface cards. The second tier moves up to the network element level, monitoring the process status, service response time, and any abnormal crashes or restarts of various software network elements related to encoding / decoding services (such as media processors and signaling controllers). The third tier further extends to the site level, monitoring the network connection status, reachability, and stability between different physical or logical sites within the private network. Through continuous monitoring of these three levels, the unit aggregates and generates a comprehensive three-tiered reliability monitoring signal, which is then transmitted to the intelligent selection module.

[0038] Furthermore, the role of this Level 3 reliability monitoring signal is proactive and strategic. It provides crucial reliability context for the intelligent selection module. For example, when the monitoring signal shows that the CPU utilization of a server continuously exceeds the safety threshold (hardware-level warning), or the response latency of a media processing network element increases abnormally (network element-level warning), or the network connected to a remote site experiences intermittent outages (site-level warning), even if the current voice call is not affected, this signal will send a clear "codec switching preparation signal" to the intelligent selection module. This allows the intelligent decision engine to anticipate risks and consciously avoid nodes or paths facing potential risks in subsequent voice routing or session establishment, prioritizing resources in a healthy state, thereby achieving fault avoidance rather than passive response. In addition to the above-mentioned structural monitoring, this unit also performs in-depth processing on the network parameter signals involved. It not only collects raw, instantaneous network quality indicators, but also performs trend analysis and statistical learning on this data. For example, it calculates whether the bandwidth fluctuation trend is stabilizing or deteriorating, analyzes whether the latency change pattern is periodic, and statistically analyzes the long-term distribution of packet loss rate. Based on these analyses, it generates a more accurate and predictive network quality forecast signal. This forecast signal, combined with the environmental state signal, provides stronger decision support for the intelligent selection module, enabling it to make more robust codec selections that adapt not only to the current situation but also to near-future network changes. Finally, the high-reliability monitoring unit establishes an efficient fault self-healing mechanism, a key feature of its high-reliability design. When it directly detects an anomaly in a specific codec instance currently serving a voice session (e.g., continuous packet loss, encoding failure, or container unresponsiveness) through real-time monitoring, this mechanism is immediately triggered. It automatically and quickly activates a preset backup codec instance in the background and, through collaboration with the management interface module, guides the voice session to seamlessly switch to the backup instance, thus completing fault recovery with almost no user awareness. This maximizes the continuity of voice services and fulfills the promise in the disclosure document to "ensure customer business continuity."

[0039] like Figure 2As shown, this is the core of the system's shift from "general-purpose" to "customized for private networks." It doesn't statically store business policies but possesses the ability to dynamically sense and analyze specific business scenarios within the private network. When the system detects that a video conferencing service is activated, this unit immediately initiates the corresponding policy adjustment process. It prioritizes codecs with low latency characteristics because audio-visual synchronization is a crucial user experience metric in video conferencing; any latency caused by codec processing can lead to communication barriers. Meanwhile, for services like enterprise address book integration, the focus may not be on ultimate audio quality or the lowest latency, but rather on broad codec compatibility and efficient signaling interaction processing. This ensures a smooth process when querying and retrieving address book information and conducting voice communication, preventing call establishment failures or anomalies due to codec compatibility issues. For office automation integration, this unit tends to select codecs with high compression rates. This is primarily because OA systems may run in complex enterprise intranet environments where network bandwidth may be shared by multiple applications; high compression rates can effectively reduce the bandwidth consumption of voice services, ensuring the smooth operation of other data services. Furthermore, this unit stores more detailed configurations of private network-specific service characteristics. For example, softphone services may have a preference for specific frequency response ranges, while electronic fax services require codecs that can effectively handle audio signals generated by modems. The private network service adaptation unit integrates these fine-grained requirements into a comprehensive private network characteristic adaptation signal. This signal is then seamlessly merged into the service policy signal and transmitted to the intelligent selection module. This allows the intelligent decision-making process to fully consider the micro-characteristics of private network services, achieving a truly service-driven codec strategy.

[0040] Specifically, the core algorithm engine of the system enables accurate and efficient selection. It employs an advanced weighted evaluation algorithm to process the three main input signals it receives: codec availability signal, environmental status signal, and service strategy signal. The complexity of this algorithm lies in its need to simultaneously weigh multiple often interdependent dimensions. The real-time network status dimension requires selecting a codec that can adapt to the current network environment with its bandwidth, latency, and packet loss; the device support capability dimension limits the selection to the set of codecs that the terminal device can handle; the service quality requirement dimension, as mentioned earlier, may emphasize low latency, high fidelity, or high compatibility; and the system resource load dimension needs to consider the current server's processing capacity to avoid selecting a codec with excessively high computational complexity that could overload the system. The multi-dimensional decision-making unit uses a built-in, configurable weight model to quantify, score, and comprehensively balance these factors, ultimately generating an optimal codec selection scheme. More importantly, this unit does not adhere to a static set of weight parameters; it possesses dynamic learning capabilities. It continuously collects feedback data on the effects of historical selections, such as the actual voice quality evaluation score after a selection, the resulting resource consumption, and whether subsequent codec switching was triggered. By analyzing this historical data, it can automatically fine-tune the weights of various parameters in the weighted evaluation algorithm, forming a continuously self-optimizing algorithm optimization signal to guide future decisions. This makes the system's selection increasingly accurate and better suited to the actual operating environment and business needs. Furthermore, this unit's decision-making is not a one-time event; it continuously monitors changes in environmental status signals throughout the entire voice conversation. Once it detects a significant change in network conditions or system load, it immediately recalculates and updates the codec selection signal in real time, ensuring that voice communication is always protected by the current optimal codec scheme.

[0041] Furthermore, the focus shifted to the system's human-computer interaction and operation and maintenance management, expanding the functionality of the management interface module and adding a visual maintenance unit. This unit is a crucial bridge, presenting the system's complex internal state and powerful management capabilities to operations and maintenance personnel in a user-friendly manner. It generates rich, graphical monitoring signals and renders them in real time on a management portal designed specifically for the system. Operations and maintenance personnel can intuitively see the entire operation of the codec system through this portal, such as real-time usage rankings of various codecs, historical performance indicator trend graphs, and heatmaps of system CPU and memory resource utilization. This visualization significantly lowers the cognitive threshold of the system, enabling operations and maintenance personnel to quickly grasp the overall situation. Beyond pure monitoring, this unit also provides a one-click maintenance operation interface. Administrators no longer need to adjust system behavior through complex command lines or configuration files; they can generate codec configuration adjustment signals and batch modify codec priorities or business policy parameters through simple operations on the graphical interface, such as dragging priority sliders and selecting business policy templates. This significantly improves operation and maintenance efficiency and reduces the risk of human error. In addition, the visual maintenance unit also has complete operation auditing functions. It automatically records all critical management operations, including the logic and results of manual intervention and automated system decisions, generating detailed operation audit signals and forming traceable maintenance logs. These logs are not only used for security auditing but also provide a valuable data foundation for subsequent analysis of system behavior and optimization of strategy configurations. Further refining resource utilization efficiency, a resource optimization component has been added to the containerized deployment unit. This component pushes the elastic scalability brought by containerization technology to a more granular and intelligent level. Based on the core concept of microservice architecture, it achieves fine-grained management of codec instances. This component continuously monitors the resource utilization efficiency of each container instance, including CPU cycles, memory usage, and network I / O. It doesn't simply increase or decrease the number of instances based on business load; it also intelligently adjusts the resource quota for each running instance. When it detects that the resource utilization of some instances is consistently below a set threshold, indicating resource waste, it automatically triggers an instance merging process, merging lighter-loaded instances into fewer containers to free up excess resources. Conversely, when it detects that the resource utilization of certain instances is consistently too high, approaching their quota limits, it immediately triggers horizontal scaling to create new instances to share the load and prevent performance bottlenecks. All these dynamic adjustment behaviors are reported to the management interface module in the form of resource allocation optimization signals, ensuring operational visibility. More importantly, this component also supports advanced features crucial in modern software delivery, such as canary releases and version rollbacks.When upgrading codecs, it can first deploy the new version to only a small number of instances to observe its stability and performance. Once confirmed to be error-free, the upgrade scope can be gradually expanded. If any issues are found with the new version, it can be quickly rolled back to the previous stable version. This greatly improves the security and smoothness of system updates and maintenance, ensuring that business continuity is not affected.

[0042] This invention relates to a voice intelligent codec management system and method based on multi-standard codecs. It addresses the aforementioned problems by constructing a system integrating a multi-standard codec library, status monitoring, service rules, intelligent selection, and management interfaces. The system first uses a status monitoring module to perceive network and device status in real time, while a service rules module provides dedicated network service policies. The intelligent selection module integrates this information and uses intelligent algorithms to dynamically select the optimal codec from the codec library. The management interface module performs configuration and provides a visual maintenance interface. This method achieves real-time and dynamic matching of codecs with network conditions, device capabilities, and service scenarios, thereby significantly improving the system's adaptability and resource utilization efficiency while ensuring voice quality.

[0043] Therefore, the voice intelligent codec management system and method based on multi-standard codecs of the present invention solves the problem of rigid voice codec schemes in industry private networks that are difficult to dynamically adapt to complex network environments.

[0044] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A voice intelligent codec management system based on multi-standard codecs, characterized in that, include: A codec library module, which stores various standard speech codecs and generates usable codec signals; The codec library module further includes a containerized deployment unit. This unit encapsulates various standard speech codecs into independent container instances, dynamically adjusts the number of container instances based on system load, and generates codec resource scheduling signals that are transmitted to the management interface module. When an increase in voice traffic is detected, the container instances are automatically expanded, and when the traffic decreases, excess container instances are automatically released, achieving elastic allocation of codec resources. It also supports hybrid deployment on private cloud platforms, public cloud platforms, and general-purpose servers. The containerized deployment unit also maintains codec lifecycle management signals, including the start, stop, and health status monitoring of codec instances, to ensure the continuous availability of codec services. The status monitoring module collects network parameter signals and device capability signals in real time and generates environmental status signals. The status monitoring module generates environmental status signals and transmits them to the intelligent selection module and management interface module. The codec library module generates codec availability signals and transmits them to the intelligent selection module. The service rules module generates service policy signals and transmits them to the intelligent selection module. The intelligent selection module generates codec selection signals and transmits them to the management interface module. The management interface module generates codec configuration signals and transmits them to the IMS core network to execute codec switching. Simultaneously, it generates monitoring display signals and transmits them to the management portal for visualized maintenance. The status monitoring module further includes a high-reliability monitoring unit. This high-reliability monitoring unit monitors server hardware resource status, network element operating status, and site connection status in real time, generating a three-level reliability monitoring signal that is transmitted to the intelligent selection module. When any level of fault is detected, a codec switching preparation signal is triggered. The high-reliability monitoring unit continuously collects network quality indicators, including bandwidth fluctuation trends, latency change patterns, and packet loss rate statistics, generating a network quality prediction signal, which is then merged with the environmental status signals and transmitted to the intelligent selection module. The high-reliability monitoring unit also establishes a fault self-healing mechanism, automatically activating a backup codec instance when a codec anomaly is detected. The business rules module stores private network business policies and generates business policy signals, wherein the private network business policies define codec priorities based on video conferencing, enterprise address book and OA integration requirements. The intelligent selection module receives codec availability signals, environmental status signals, and service policy signals, and generates codec selection signals through multi-dimensional weighted calculations using intelligent algorithms. The intelligent algorithms dynamically optimize the selection based on network conditions, device capabilities, and service requirements. The management interface module receives codec selection signals and environmental status signals, and generates codec configuration signals and monitoring display signals. The codec configuration signals are used to configure and apply the selected codec in a voice session, and the monitoring display signals are used to display codec performance statistics and operation interfaces in real time in the management portal.

2. The intelligent voice codec management system based on multi-standard codecs according to claim 1, characterized in that, The business rules module further includes a private network business adaptation unit. The private network business adaptation unit dynamically adjusts the business strategy signal according to the private network application scenario. For video conferencing services, it prioritizes low-latency codecs; for enterprise address book integration services, it prioritizes high-compatibility codecs; and for office automation integration services, it prioritizes high-compression codecs. The private network business adaptation unit also stores private network-specific business characteristic configurations, including softphone service preference settings and electronic fax service requirement parameters, forming a private network characteristic adaptation signal and merging it into the business strategy signal for transmission to the intelligent selection module.

3. The intelligent voice codec management system based on multi-standard codecs according to claim 1, characterized in that, The intelligent selection module further includes a multi-dimensional decision-making unit. This multi-dimensional decision-making unit uses a weighted evaluation algorithm to process codec availability signals, environmental status signals, and service policy signals. The weighted evaluation algorithm comprehensively considers four dimensions of factors: real-time network conditions, equipment support capabilities, service quality requirements, and system resource load, to generate the optimal codec selection scheme. The multi-dimensional decision-making unit also has dynamic learning capabilities, continuously optimizing the weighting parameters based on historical selection results to form an algorithm optimization signal for adjusting subsequent decision-making processes. During the session, the multi-dimensional decision-making unit continuously monitors environmental changes and updates the codec selection signal in real time.

4. The intelligent voice codec management system based on multi-standard codecs according to claim 1, characterized in that, The management interface module further includes a visual maintenance unit, which generates graphical monitoring display signals to show the usage status, performance statistics, and system resource consumption of each codec in real time in the management portal. The visual maintenance unit provides a one-click maintenance operation interface, receives administrator commands to generate codec configuration adjustment signals, and supports batch modification of codec priority and business strategy parameters. The visual maintenance unit also generates operation audit signals to record all management operations and system automatic decision-making processes, forming a traceable maintenance log for subsequent analysis and optimization.

5. The intelligent voice codec management system based on multi-standard codecs according to claim 1, characterized in that, The containerized deployment unit further includes a resource optimization component. This resource optimization component implements fine-grained management of codec instances based on a microservice architecture. It automatically adjusts container resource quotas according to voice service load, forming a resource allocation optimization signal that is transmitted to the management interface module. The resource optimization component monitors the resource utilization efficiency of container instances. When it detects that the resource utilization rate is lower than a threshold, it automatically merges instances. When the resource utilization rate is consistently too high, it automatically triggers horizontal scaling. The resource optimization component also supports canary releases and version rollback functions for codec instances.

6. The intelligent voice codec management system based on multi-standard codecs according to claim 1, characterized in that, The high-reliability monitoring unit further includes a failover component. The failover component establishes a redundant backup mechanism for codec instances. When a failure is detected in the currently used codec instance, it automatically switches to the standby instance and sends a switchover completion signal to the management interface module. The failover component enables cross-server codec instance disaster recovery. When the primary server fails, the codec service is automatically migrated to the standby server. The failover component also provides a manual switchover function, allowing administrators to actively trigger codec instance switchover operations through the management interface module.

7. The intelligent suppression management method for a speech intelligent codec management system based on multi-standard codecs according to any one of claims 1-6, comprising: S1: Stores multiple standard speech codecs and generates usable signals for the codecs; S2: Real-time acquisition of network parameter signals and device capability signals and generation of environmental status signals, where network parameter signals include bandwidth, latency and packet loss rate information, and device capability signals include terminal type and supported codec information; S3: Store private network service policies and generate service policy signals, where the private network service policies define codec priorities based on video conferencing, enterprise address book and OA integration requirements. S4: Receive codec availability signals, environmental status signals, and service policy signals, and generate codec selection signals through multi-dimensional weighted calculations using intelligent algorithms. The intelligent algorithms dynamically optimize the selection based on network conditions, device capabilities, and service requirements. S5: Receives codec selection signal and environment status signal, generates codec configuration signal and monitoring display signal, wherein the codec configuration signal is used to configure and apply the selected codec in the voice session, and the monitoring display signal is used to display codec performance statistics and operation interface in real time in the management portal.

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