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We propose a text classification method for the purpose of creating a language model for automatic recognition of spontaneous spoken speech. Transcripts from our departmental speech database served as spontaneous spoken texts. Using supervised machine learning methods, we have created multiple classification models (including neural networks), that were able to distinguish them from written texts with high accuracy. We subsequently verified the accuracy of our trained models on a database of texts containing direct speech extracted from newspaper articles.

eISSN:
1338-4287
ISSN:
0021-5597
Langue:
Anglais
Périodicité:
2 fois par an
Sujets de la revue:
Linguistics and Semiotics, Theoretical Frameworks and Disciplines, Linguistics, other