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Sensitive word uncertainty resolving method for voice recognition application system

A speech recognition and application system technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of poor shareability of speech recognition modules, inability to know input nodes, no shareability, etc., and achieve a good human-computer interaction experience Effect

Active Publication Date: 2014-11-26
上海和汇安全用品有限公司 +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] 2) Different applications work independently, and the sharing of speech recognition modules is poor
Moreover, each application program develops a set of speech recognition subsystems separately, and there is no sharing
Different applications cannot know each other's input nodes, especially the detailed input node list, so it is difficult to truly share the speech recognition module

Method used

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  • Sensitive word uncertainty resolving method for voice recognition application system
  • Sensitive word uncertainty resolving method for voice recognition application system
  • Sensitive word uncertainty resolving method for voice recognition application system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] Such as figure 1 , figure 2 As shown,

[0058] figure 1 The sensitive vocabulary in the smart system is mobilized and configured flexibly by the application on the intelligent system, effectively solving the problem of the unknown of sensitive words. The A7 system issues an interrupt to the main system A15 according to the result of the speech recognition algorithm; the main system A15 interrupts the service program correspondingly, and transfers the speech recognition result and the corresponding application process id and other information to the operating system memory core area of ​​the main system A15; A new system process is added to the operating system of system A15, which periodically queries the memory core area, and informs the corresponding application process by means of inter-process communication; the application process, according to the received message, makes corresponding actions, that is The mapping of messages to input nodes is completed.

[0059] fig...

Embodiment 2

[0061] Such as image 3 As shown, only one CPU is used in this embodiment. image 3 The five modules in A)B)C)D)E) are the changes to the operating system. F) "Sensitive vocabulary and attached speech recognition module" in the figure is a hardware module, which can process speech recognition independently of the CPU (or co-processing) and send out interrupt signals in a timely manner according to the algorithm results; the corresponding interrupt service program will Voice recognition results and corresponding application process id and other information are transferred to the operating system memory core area; the operating system adds a new system process, periodically queries the memory core area, and informs the corresponding application process through inter-process communication; application The process, according to the received message, makes the corresponding behavior response, that is, completes the mapping of the message to the input node. Similarly, for application...

Embodiment 3

[0064] Such as Figure 4 As shown, Embodiment 3 does not require the hardware module of “sensitive vocabulary and auxiliary speech recognition module” in Embodiment 2, and only needs to modify and supplement the existing operating system. Figure 4 The five modules in A)B)C)D)E) are the changes to the operating system. Figure 4 The voice recognition processing process in the medium uses recognition algorithms to process the input voice signals, and transports the voice recognition results and the corresponding application process id and other information to the operating system memory core area; the operating system adds new system processes to periodically query the memory core area, And notify the corresponding application process by means of inter-process communication; the application process, according to the received message, makes corresponding behavioral responses, that is, completes the mapping of the message to the input node. Similarly, for applications, the sensitive...

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Abstract

The invention relates to the technical field of intelligent information processing, in particular to a sensitive word uncertainty resolving method for a voice recognition application system. A sensitive word list is introduced into a recognition algorithm, time resources and space resources required by voice recognition are reduced, and the sensitive word list is a subset of a set of all sensitive words; the sensitive word list is updated continuously by application programs according to the progress of human-computer interaction and changes of the application scene; the corresponding application program course is informed of the result that a voice recognition algorithm is performed on the sensitive word list through an interactive mechanism modified by an operating system. The sensitive word uncertainty resolving method for the voice recognition application system has the advantages that the sensitive word list is introduced into the recognition algorithm, and thus resources required by each frame of voice recognition are reduced; the sensitive word list is updated continuously by the application programs, and thus good human-computer interaction experience is kept; the corresponding application program course is informed of the recognition result through the modified interactive mechanism, and thus all the application programs can share a voice recognition function module without consuming time resources.

Description

[Technical Field] [0001] The invention relates to the technical field of intelligent information processing, in particular to a method for solving the unknownness of sensitive words of a speech recognition application system. [Background technique] [0002] Various contemporary speech recognition technology methods are roughly similar, usually divided into front-end processing, acoustic pattern training, and pattern matching (decoder). The most common front-end processing is to do endpoint detection (detect energy, find the starting point of the speech) and speech enhancement (denoise, increase the signal-to-noise ratio). The decoder is one of the cores of the speech recognition system. Its task is to find the word string that can output the signal with the greatest probability according to the acoustic, language model and dictionary for the input signal. The model of a speech recognition system usually consists of an acoustic model and a language model, which correspond to the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/20
Inventor 徐彬宸
Owner 上海和汇安全用品有限公司
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