Generation method and device of word segmentation training set

Abstract

The invention provides a generation method and device of a word segmentation training set. The generation method of the word segmentation training set comprises the following steps: obtaining training corpus, adopting different word segmentation devices to independently carry out word segmentation on different training corpuses to obtain word segmentation results corresponding to different word segmentation devices; dividing the word segmentation results into accurate matching word segmentation results and non accurate matching word segmentation results; and according to the word segmentation results, carrying out noise reduction processing on the non accurate matching word segmentation results to obtain the word segmentation training set. The method can lower time and cost for the generation of the word segmentation training set, is low in implementation cost and improves effect.

Description

technical field [0001] The invention relates to the technical field of speech processing, in particular to a method and device for generating a word segmentation training set. Background technique [0002] Speech synthesis, also known as Text to Speech (TTS), can convert text information into speech and read it out in real time, which is equivalent to installing an artificial mouth on a machine. For speech synthesis systems, the input text needs to be processed first, including word segmentation. There are two main types of word segmentation algorithms, one is an algorithm based on dictionary matching, and the other is a learning algorithm based on training corpus. [0003] In the prior art, a conditional random field (Conditional Random Field, CRF) model is a mainstream learning algorithm based on training corpus. However, the CRF model is a supervised machine learning algorithm that requires a large amount of manually labeled data as support. The work of using human lab...

AI Technical Summary

Problems solved by technology

Using human labor to do data labeling is very expensive both economically and time-consuming

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