Voice transmission plays a crucial role in many applications such as e.g. telecommunications. An alternative to increase the efficiency of voice transmission is using a codification that permits compressing the signal to be transmitted. Such a compression assumes data sets with basic forms, whose combination produce the voice signal. Generally this data set is organized around an array of data, known as codebook. The codebook is constructed by a vectorial quantization process, which consists of looking for what vectors are most representatives, within a set. Next a structure of data is created that stores the vectors, also known as centers. Then, given a codebook with the most representative basic forms, the problem is translated to take a piece of voice, look for its position and transmit it. Since the receiver will have the same structure of data the voice will be able to be synthesized. The problem consists in the search in the codebook, which can be expensive in terms of computation and other resources, which perform operation in real time, characteristic that in some services is fundamental, for example in telecommunication. In this work we present a new algorithm to construct and to cross codebooks by using a data mining tool such as self organizing maps over a database of humans voices. This algorithm produces a codebook structure within a relation of proximity between its elements, reducing the problem to a local search, which allows to decrease compression time and to reduce the rate of transmitted bits.
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