Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Adaptive speech characteristic model training method of aviation cabin environment

A technology of speech features and model training, applied in speech analysis, speech recognition, instruments, etc., can solve problems such as low recognition rate, and achieve the effect of improving recognition rate

Pending Publication Date: 2017-09-15
SHANGHAI AVIATION ELECTRIC
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the problem of low recognition rate in the prior art and provide a novel training method for the adaptive speech feature model of the aviation cockpit environment

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Adaptive speech characteristic model training method of aviation cabin environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0028] See figure 1 , shown in the figure is an aviation cockpit environment adaptive speech feature model training method. The method performs the following steps in sequence:

[0029] Step S1, collecting personal adaptive speech features.

[0030] Step S11, simulating the aviation cockpit environment, and inputting personal adaptive voice data.

[0031] In step S12, the personal adaptive voice data is designed as 16k sampling 16bit voice data, and the environment of an aviation cockpit is simulated for collection.

[0032] Step S13, extracting personal adaptive speech features:

[0033] Step S131, acquiring frame number voice data.

[0034] Step S132, designing the frame-number voice data as 400 sampling points per frame.

[0035] In step S133 , the 75-dimensional Mel frequency scale coefficient (MFC) is used as the speech...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an adaptive speech characteristic model training method of an aviation cabin environment. The method comprises the steps of S1, acquiring a personal adaptive speech characteristic; S2, supplying a personal adaptive speech mark; S3, supplying a basic characteristic model; S4, utilizing a deep neural network (DNN) adaptive algorithm, updating the basic characteristic model according to the personal adaptive speech characteristic and the corresponding personal adaptive speech mark, thereby generating an adaptive model; S5, performing identification testing, and verifying improving capability of the adaptive model to personal speech identification; and S6, performing model packaging for generating a personal characteristic database. The adaptive speech characteristic model training method has advantages of updating the basic characteristic model through the personal adaptive speech characteristic, generating the adaptive model with higher identification capability, and effectively improving identification rate of avionics speech products.

Description

technical field [0001] The invention relates to the field of speech recognition, in particular to an aviation cockpit environment adaptive speech feature model training method, which has a remarkable effect on improving the recognition rate of avionics speech products. Background technique [0002] With the rapid development of electronic technology and aircraft technology, the field of man-machine system technology based on cognition / perception is one of the ten key fields of avionics technology in the future, and speech recognition technology is based on the technology of man-machine system of cognition / perception. A very important key technology. At present, the existing speech recognition is mainly designed for standard speech. If the driver's speech is not standard or has personal characteristics, the recognition rate is often low. How to make voice recognition technology truly help pilots to complete the control of the aircraft has become the key to the practical appl...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/06G10L15/07G10L15/16
CPCG10L15/063G10L15/07G10L15/16
Inventor 温泉姚竞黄梅娇
Owner SHANGHAI AVIATION ELECTRIC
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com