Abstract
The question that we investigate in this paper is, whether it is possible for Genetic Programming to extract certain regularities from raw time series data of human speech. We examine whether a genetic programming algorithm can find programs that are able to discriminate certain spoken vowels and consonants. We present evidence that this can indeed be achieved with a surprisingly simple approach that does not need preprocessing. The data we have collected on the system’s behavior show that even speaker-independent discrimination is possible with GP.
Keywords
- Genetic Programming
- Recognition Rate
- Finite Impulse Response
- Automatic Speech Recognition System
- Machine Code
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Conrads, M., Nordin, P., Banzhaf, W. (1998). Speech sound discrimination with genetic programming. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds) Genetic Programming. EuroGP 1998. Lecture Notes in Computer Science, vol 1391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055932
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DOI: https://doi.org/10.1007/BFb0055932
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