title: Obtaining phonetic transcriptions: a comparison between expert listeners and a continuous speech recognizer.
abstract: In this article, we address the issue of using a continuous speech recognition tool to obtain phonetic or phonological representations of speech. Two experiments were carried out in which the performance of a continuous speech recognizer (CSR) was compared to the performance of expert listeners in a task of judging whether a number of prespecified phones had been realized in an utterance. In the first experiment, nine expert listeners and the CSR carried out exactly the same task: deciding whether a segment was present or not in 467 cases. In the second experiment, we expanded on the first experiment by focusing on two phonological processes: schwa-deletion and schwa-insertion. The results of these experiments show that significant differences in performance were found between the CSR and the listeners, but also between individual listeners. Although some of these differences appeared to be statistically significant, their magnitude is such that they may very well be acceptable depending on what the transcriptions are needed for. In other words, although the CSR is not infallible, it makes it possible to explore large datasets, which might outweigh the errors introduced by the mistakes the CSR makes. For these reasons, we can conclude that the CSR can be used instead of a listener to carry out this type of task: deciding whether a phone is present or not.
authors.affiliation: Department of Language and Speech, University of Nijmegen, The Netherlands. M.Wester@let.kun.nl
authors.forename: M
authors.initials: M
authors.lastname: Wester
authors.forename: J M
authors.initials: JM
authors.lastname: Kessens
authors.forename: C
authors.initials: C
authors.lastname: Cucchiarini
authors.forename: H
authors.initials: H
authors.lastname: Strik
mesh_terms: D016208:Databases, Factual; D001330:Electronic Data Processing; D006801:Humans; D008037:Linguistics / Q000379:methods*; D010700:Phonetics; D013060:Speech; D018709:Statistics, Nonparametric