Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Language identification method and identification system

A language recognition and language technology, applied in speech recognition, speech analysis, instruments, etc., can solve problems such as language recognition system performance degradation, and achieve the effect of improving performance

Active Publication Date: 2019-11-29
SHENZHEN OCTOPUS TECH
View PDF3 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a language recognition method and recognition system to solve the problem that the back end of the language recognition system existing in the prior art uses N-gram-based language models to model the phoneme structure information of different languages , leading to the performance degradation of the language recognition system

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
  • Language identification method and identification system
  • Language identification method and identification system
  • Language identification method and identification system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0040] Such as figure 1 As shown, the language recognition method provided by the embodiment of the present invention includes:

[0041] S101, converting each frame of speech signal into pronunciation attribute features;

[0042] S102, using the pronunciation attribute feature to train a Time Delay Neural Network (Time Delay Neural Network, TDNN), wherein the pronunciation attribute feature is input into the time delay neural network, and the time delay neural network learns the input pronunciation attribute feature and classification, to obtain the distribution of each language in the pronunciation attribute feature space, that is, the language model;

[0043] S103, when performing language recognition, input the pronunciation attribute characteristics of the speech to be recognized into the trained time-delay neural network, and the output result of the time-delay neural network is the similarity between the speech to be recognized and each language model, wherein the similar...

Embodiment 2

[0096] The present invention also provides a specific implementation of a language recognition system. Since the language recognition system provided by the present invention corresponds to the specific implementation of the aforementioned language recognition method, the language recognition system can perform the process steps in the specific implementation of the above method To achieve the purpose of the present invention, therefore, the explanations in the specific implementation of the above-mentioned language recognition method are also applicable to the specific implementation of the language recognition system provided by the present invention, and will not be repeated in the following specific implementation of the present invention.

[0097] Such as Figure 4 As shown, the embodiment of the present invention also provides a language recognition system, including:

[0098] Pronunciation attribute extractor 11, is used for converting each frame of speech signal into p...

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 provides a language identification method and identification system, and can improve performance of the language identification system. The method comprises the steps of: converting eachframe of voice signal into a pronunciation attribute characteristic; training a time delay neural network by utilizing the pronunciation attribute characteristics, wherein the pronunciation attributecharacteristics are input into the time delay neural network, the time delay neural network carries out learning and classification on the input pronunciation attribute characteristics to obtain distribution of each language in a pronunciation attribute characteristic space, i.e., a language model; and when carrying out language identification, inputting a pronunciation attribute characteristic of to-be-identified voice into the trained time delay neural network, and obtaining an output result of the time delay neural network, which is a similarity between the to-be-identified voice and eachlanguage model, wherein the language model with the highest similarity is a language category of the to-be-identified voice. The invention relates to the technical field of voice identification.

Description

technical field [0001] The invention relates to the technical field of speech recognition, in particular to a language recognition method and a recognition system. Background technique [0002] Language recognition refers to the process of using a computer to automatically identify or confirm the language category of a speech segment. An effective language recognition system can be widely used in the front end of multilingual speech recognition systems and automatic translation systems. There are many features that can be used to distinguish languages, including: acoustic features, prosodic features, phoneme structure features, morphological features, and syntactic features. [0003] Existing language recognition methods can be divided into two categories according to the characteristics used: ① Spectrum-based language recognition methods. ② Language recognition method based on token. Spectrum-based language recognition methods take advantage of the differences in the dis...

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): G10L15/00G10L15/02G10L15/06G10L15/16
CPCG10L15/005G10L15/02G10L15/063G10L15/16
Inventor 张劲松于嘉威解焱陆
Owner SHENZHEN OCTOPUS TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
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