Componentized Voice Server Speech Detection
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Solution Overview
Problem
Conventional voice servers rely on processor-intensive software-based speech detection routines, which inefficiently use scarce resources and fail to leverage external hardware-based detection mechanisms, leading to suboptimal performance and resource consumption.
Innovation Solution
A pluggable, configurable speech detection component is integrated with internal software-based routines, allowing for selective use of external hardware-based detection mechanisms, such as energy difference detection in telephone channels, to enhance speech detection accuracy and resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If software-based speech detection routines are used to improve speech detection accuracy, then detection precision is improved, but processor and memory consumption increases
Solution Approach 1:
The speech detection function is segmented into two separate components: hardware-based detection (energy level monitoring) and software-based detection (detailed speech analysis). The hardware component handles initial detection to reduce processor load, while the software component provides accurate speech recognition when needed, thus resolving the contradiction between detection accuracy and resource consumption.
Solution Approach 2:
A hardware-based speech detection component acts as an intermediary between the telephony channel and the software-based speech detection routines. This intermediary performs preliminary energy level monitoring and filtering, reducing the burden on the processor-intensive software routines while maintaining overall detection accuracy.
2Productivity
If hardware-based speech detection is used to reduce processor load, then resource efficiency is improved, but speech detection capability is reduced
Solution Approach 1:
The patent merges hardware-based speech detection (energy level monitoring) with software-based speech detection (detailed analysis) into a unified system. The hardware component provides efficient initial detection to reduce processor load, while the software component supplements with accurate speech recognition, achieving both resource efficiency and comprehensive detection capability.
Solution Approach 2:
The system dynamically adjusts the balance between hardware and software detection based on operational needs. The configurable parameters allow the system to switch between hardware-only, software-only, or combined detection modes, enabling flexible adaptation to different resource availability and detection requirement scenarios.
3Reliability
If internal software-based speech detection is used to ensure detection reliability, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The detection system is segmented into independent hardware and software modules with clearly defined interfaces. This segmentation allows each component to be optimized separately for its specific function while maintaining overall system reliability through the coordinated operation of both modules.
Solution Approach 2:
The voice server is designed with universal architecture that can accommodate both hardware-based and software-based detection methods through a unified interface. This multi-functionality allows the system to reliably perform speech detection regardless of which detection method is used or combined, reducing overall system complexity despite the added capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient use of resources by allowing customers to configure speech detection settings, reducing processor load and improving detection accuracy by combining internal and external detection methods, thereby optimizing voice server performance.
Implementation Method 1
hardware-based techniques can monitor signal energy levels within telephony channels and differentiate speech utterances from silence and/or noise based upon differences in the signal energy levels
Data Source
AI summary
A method for detecting speech utterances within a telephone call can include the steps of initializing a componentized voice server having at least one software-based speech detection routine. At least one previously established parameter can be used to discern a speech detection methodology for handling an incoming call. The software-based speech detection routine can be set in accordance with a select one of the parameters. An indicator of particular one of the parameters can be conveyed to an external speech detection component so that the external speech detection component is set to detect speech for the call in accordance with the conveyed indication. The software-based speech detection routine and/or the external speech detection component can detect a speech utterance for the call. The voice server can perform at least one programmatic action responsive to the detecting of the speech utterance.