Recent research on the TIMIT corpus suggests th at longer-length acoustic models are more appropriate for pronunciation variation modelling than the context-dependent phones th at conventional autom atic speech recognisers use. However, the impressive speech recognition results obtained with longer-length models on TIMIT rem ain to be reproduced on other corpora. To understand the conditions in which longer-length acoustic models result in considerable im provem ents in recognition performance, we carry out recognition experiments on both TIMIT and the Spoken D utch C orpus and analyse the differences between the two sets of results. We establish th at the details o f the procedure used for initialising the longer-length models have a substantial effect on the speech recognition results. W hen initialised appropriately, longer-length acoustic models that borrow their topology from a sequence of triphones cannot capture the pronunciation variation phenom ena th at hinder recognition perform ance the most.

This paper presents a study of European Portuguese elderly speech, in which the acoustic characteristics of two groups of elderly speakers (aged 60-75 and over 75) are compared with those of young adult speakers (aged 19-30). The correlation between age and a set of 14 acoustic features was investigated, and decision trees were used to establish the relative importance of the features. A greater use of pauses characterized speakers aged 60 and over. For female speakers, speech rate also appeared to correlate with age. For male speakers, jitter distinguished between speakers aged 60-75 and older. The correlation between the features and speech recognition performance was also investigated. Word error rate correlated mostly with the use of pauses, speech rate, and the ratio of long phone realizations. Finally, by comparing the phone sequences used by the recognizer on the most frequent words, we observed that the young adult speakers reduced schwas more than the elderly speakers. This result seems to confirm the common idea that young speakers reduce articulation more than older speakers. Further investigation is needed to confirm this result by determining whether this is due to ageing or to the generation gap.

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The following full text is a publisher's version.For additional information about this publication click this link. http://hdl.handle.net/2066/44459Please be advised that this information was generated on 2024-06-02 and may be subject to change. Article 25fa End User AgreementThis publication is distributed under the terms of Article 25fa of the Dutch Copyright Act. This article entitles the maker of a short scientific work funded either wholly or partially by Dutch public funds to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.Research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act, are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.

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Articulatory and acoustic reduction can manifest itself in the temporal and spectral domains. This study introduces a measure of spectral reduction, which is based on the speech decoding techniques commonly used in automatic speech recognizers. Using data for four frequent Dutch affixes from a large corpus of spontaneous face-to-face conversations, it builds on an earlier study examining the effects of lexical frequency on durational reduction in spoken Dutch [Pluymaekers, M. et al. (2005). J. Acoust. Soc. Am. 118, [2561][2562][2563][2564][2565][2566][2567][2568][2569], and compares the proposed measure of spectral reduction with duration as a measure of reduction. The results suggest that the spectral reduction scores capture other aspects of reduction than duration. While duration can-albeit to a moderate degreebe predicted by a number of linguistically motivated variables (such as word frequency, segmental context, and speech rate), the spectral reduction scores cannot. This suggests that the spectral reduction scores capture information that is not directly accounted for by the linguistically motivated variables. The results also show that the spectral reduction scores are able to predict a substantial amount of the variation in duration that the linguistically motivated variables do not account for.

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