Method for identifying all languages by voice and inputting individual characters by voice

Abstract

The invention provides a method for identifying all languages by voice and inputting individual characters by voice. The invention is characterized by representing m inhomogeneities with a group of m unknown or known different monotones; pronouncing common single words once; converting the pronunciation of each single word into a linearity preestimate coding cepstrum matrix; classifying the common words into one type in m types by a bayesian classification method or a distance classification method; looking for F most similar unknown monotones from the m unknown monotones by the bayesian classification method or the distance classification method after a user pronounces a single word tone; and arranging all single words according to the degree of similarity and letters (or stroke number) of the single word to be pronounced in F types represented by the F similar unknown monotones; and the words required can be found quickly after the user pronounced. The invention has the advantages that the method is simple, a sample is not required, typewriting is not required, each person can be qualified, the words with non-standard pronunciation or mispronunciation also can be input, the speed is rapid, and the accuracy rate is high.

Description

technical field [0001] There are 408 single tones in Chinese, plus four tones, modern phonetic methods cannot recognize 408×4 single tones, and there are more in English. The present invention divides commonly-used characters into m (=500) or so different similar-sound groups (categories), and each class of similar-sounding characters is represented by an unknown similar-sounding group. The user pronounces a single word, and the present invention finds several unknown single sounds most similar to the pronunciation of the single word in the unknown single sounds of m classes by Bayesian classification method, and then from the class represented by these similar unknown single sounds Find the desired word and sentence in the single word. [0002] The present invention uses 12 elastic frames (windows), equal length, no filter, no overlap, and converts a single-tone sound wave of different lengths into a 12*12 linear predictive coded cepstrum (LPCC) matrix. [0003] The present...

AI Technical Summary

Problems solved by technology

However, the compression process is complex and time-consuming, and it is difficult to compress the same features of the same tone to the same time position, and it is difficult to identify similar tones

As for voice input text, there is no way at present, because the current computer voice recognition is not very good

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