Abstract
In this paper, we consider the extraction of speaker identity (first name and last name) from audio records of broadcast news. Using an automatic speech recognition system, we present improvements for a method which allows to extract speaker identities from automatic transcripts and to assign them to speaker turns. The detected full names are chosen as potential candidates for these assignments. All this information, which is often contradictory, is described and combined in the Belief Functions formalism, which makes the knowledge representation of the problem coherent. The Belief Function theory has proven to be very suitable and adapted for the management of uncertainties concerning the speaker identity. Experiments are carried out on French broadcast news records from a French evaluation campaign of automatic speech recognition.
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Petitrenaud, S., Jousse, V., Meignier, S., Estève, Y. (2010). Identification of Speakers by Name Using Belief Functions. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods. IPMU 2010. Communications in Computer and Information Science, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14055-6_19
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DOI: https://doi.org/10.1007/978-3-642-14055-6_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14054-9
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