Speech recognition method and device

A speech recognition and speech conversion technology, applied in speech recognition, speech analysis, instruments, etc., can solve the problems of low clustering accuracy, no iterative method, slow recognition speed, etc., to reduce the number of Gaussians, improve the evaluation speed and accuracy rate, the effect of improving accuracy

Inactive Publication Date: 2016-08-24
LE SHI ZHI ZIN ELECTRONIC TECHNOLOGY (TIANJIN) LTD
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Clustering accuracy is low
[0007] 2. When clustering, the mean and variance of the member Gaussians are directly used as the input of the clustering. When training the clustering Gaussians, the mean and variance are directly made a simple arithmetic mean, and the clustering accuracy is extremely low.
[0008] 3. When clustering, there is no effective iterative method, causing the cluster to converge to a local optimum
[0009] 4. The Gaussian selection during recognition cannot be dynamically updated, resulting in too many member Gaussians remaining in the calculation, and the recognition speed is slow

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
  • Speech recognition method and device
  • Speech recognition method and device
  • Speech recognition method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In order to make the object, technical solution and advantages of the present invention clearer, various embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, those of ordinary skill in the art can understand that, in each implementation manner of the present invention, many technical details are provided for readers to better understand the present application. However, even without these technical details and various changes and modifications based on the following implementation modes, the technical solution claimed in each claim of the present application can be realized.

[0045] The purpose of speech recognition is to give the most likely text when a speech signal is observed. Such as figure 1 As shown, a recognition system based on HMM+GMM reads a piece of speech frame by frame, and the system converts each frame of speech signal into a feature vector. The system combines the feature vecto...

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 relates to the speech technology and discloses a speech recognition method and device. The method comprises the following steps: carrying out soft clustering calculation in advance according to N Gausses obtained through model training to obtain M soft clustering Gausses; during speech recognition, carrying out speech conversion to obtain feature vectors, and carrying out calculation according to the feature vectors to obtain the front L soft clustering Gausses, the scores of which are highest, wherein the L is smaller than M; and carrying out acoustic model likelihood calculating with each member Gauss in the L soft clustering Gausses serving as the Gauss needing to participate in calculation in an acoustic model in the speech recognition process. The method adopts a dynamic Gauss selection mode during speech recognition, thereby reducing the number of the Gausses needing to be evaluated in the acoustic model in the speech recognition process, and improving speed and accuracy of likelihood evaluation of the acoustic model.

Description

technical field [0001] The invention relates to speech technology, in particular to a speech recognition method. Background technique [0002] With the development of speech recognition technology, the accuracy of speech recognition technology has made great progress in recent years with the promotion of deep learning, especially in cloud-based services. Most of the existing speech recognition services are implemented in the cloud, and the speech needs to be uploaded to the server, and the server performs acoustic evaluation on the uploaded speech to give the recognition result. In order to improve the recognition rate, most servers use deep learning methods to evaluate speech. However, deep learning requires huge computing resources and is not suitable for local or embedded devices. And in many usage scenarios that cannot be connected to the Internet, they can only rely on local speech recognition technology. Due to limited local computing and storage resources, Hidden M...

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): G10L15/14
CPCG10L15/14G10L15/183G10L15/063G10L15/142G10L2015/0631G10L15/10G10L25/39
Inventor 王育军侯锐
Owner LE SHI ZHI ZIN ELECTRONIC TECHNOLOGY (TIANJIN) LTD
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
Try Eureka
PatSnap group products