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D–M Soundex is sometimes referred to as "Jewish Soundex" or "Eastern European Soundex", [17] although the authors discourage the use of those names. The D–M Soundex algorithm can return as many as 32 individual phonetic encodings for a single name. Results of D-M Soundex are returned in an all-numeric format between 100000 and 999999.
Daitch–Mokotoff Soundex (D–M Soundex) is a phonetic algorithm invented in 1985 by Jewish genealogists Gary Mokotoff and Randy Daitch.It is a refinement of the Russell and American Soundex algorithms designed to allow greater accuracy in matching of Slavic and Yiddish surnames with similar pronunciation but differences in spelling.
Let be a set called the instance space or the encoding of all the samples. In the character recognition problem, the instance space is X = { 0 , 1 } n {\displaystyle X=\{0,1\}^{n}} . In the interval problem the instance space, X {\displaystyle X} , is the set of all bounded intervals in R {\displaystyle \mathbb {R} } , where R {\displaystyle ...
Soundex, which was developed to encode surnames for use in censuses. Soundex codes are four-character strings composed of a single letter followed by three numbers. Daitch–Mokotoff Soundex, which is a refinement of Soundex designed to better match surnames of Slavic and Germanic origin. Daitch–Mokotoff Soundex codes are strings composed of ...
Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation. [1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. [1]
Speech coding is an application of data compression to digital audio signals containing speech.Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modeled parameters in a compact bitstream.