Evolution of communicating individuals

Authors:
Leonardo Bocchi;Sara Lapi;Lucia Ballerini
Affiliations:
Dept. of Electronics and Telecommunications, Univ. of Florence, Italy;Dept. of Electronics and Telecommunications, Univ. of Florence, Italy;School of Informatics, University of Edinburgh, UK
Venue:
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Year:
2010

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Fundamentals of speech recognition

Fundamentals of speech recognition
Deriving vocal-tract area functions from midsagittal profiles and formant frequencies: a new model for vowels and fricative consonants based on experimental data

Speech Communication

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Abstract

Verbal communication between individuals requires the parallel evolution of a vocal system capable of emitting different sounds and of an auditory system able to recognize each vocal pattern. In this work we present the evolution of a population of twins where the selection pressure is based on the ability of learning a communication pattern which allows verbal transmission of information. The fitness of each pair of twins (i.e. individuals having the same genotype) is based on the percentage of correct recognition of the perceived sounds. Results indicate the evolved communication system, in absence of noise, rapidly evolves and reaches almost 100% correct classifications, while, even in presence of a strong noise either in the channel, or in the sound generation parameters, the system can obtain a very good performance (approximately 80% correct classifications in the worst case).