[Retracted] Intelligent English Translation Based on Intelligent Speech Waveform Analysis

Algorithm 1

Determines the initial sampling point.

	Input: a sample set with N types of data.
	Output: a set of initial sample points.
	Step 1:
	For the sample set with N types of data, the overlapping point set is obtained through the algorithm.
(2)	It is assumed that the number of overlapping points is K, a vector can be formed between any two points, and K overlapping points can form vector groups .
(3)	For M vectors, the absolute value of the cosine value of the angle between the vectors is calculated as the similarity between the vectors. The formula is as follows:
	.
(4)	The similarity between vectors in the same linear English speech waveform distribution will be close to 1, and the similarity between vectors in different linear English speech waveform distributions will be close to 0. Therefore, N groups of vectors with higher similarity can be obtained according to the similarity between the vectors, and at the same time, N groups of data point sets on the same linear English speech waveform distribution can be obtained.