Abstract
In this paper, the aim is to investigate weather or not that changing the filter-bank components (of the speaker recognition system) could improve the system performance in identifying the speaker. The filter is composed of 30 Gamatone filter channels. First, the channels are mel distributed of the frequency line. Then the components´values (center frequencies and bandwidths) changes with each run. Genetic algorithm (GA) is adopted to improve the filter component values that, in a result, improve the system performance. At each GA run, a new set of filter components will be generated that aimed to improve the performance comparing with the previous run. This will continue until the system reach to the maximum accuracy or the GA reach to its limits. Results show that the system will be improved at each run, however, different words might response differently to the system filter changing. Also, in terms of additive noise, the results show that although the digits affected differently by the noise, the system still get improving with reach GA run.
Highlights
The speaker recognition system is, in general, the practical application of the speech-print idea presented by Kersta [1]
Each speaker contribute in five recoding sessions with five repetitions each. each contains The first two sessions (10 repetitions) are used in the training stage and the speech from the other sessions are used in testing stage
Method and the modulation components presented in speech signal on order to extract and estimate the speaker features presented in speech signal
Summary
The speaker recognition system is, in general, the practical application of the speech-print idea presented by Kersta [1]. This idea open the door to the researchers to pay more attention the speech signal and find out the main characteristic that characterize one person from another. Parameterization is the way of converting the speech into the set of parameters that are highly related to the problem in hand and ignoring any other features carried by the speech signal. The proposed strategy is to use the genetic algorithm along with the AM-FM parameter model in order to extract a set of parameters that are use for speaker identification system.
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