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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(More)
– In this work we focus on the design of reduced-complexity sensor compensation modules based on learning-from-examples techniques. A Multi-Objective Optimization design framework is proposed , where system complexity and compensation uncertainty are considered as two conflicting costs to be jointly minimized. In addition , suitable statistical techniques(More)
In this work we propose the use of Functional Data Analysis (FDA) as a powerful methodology to tackle problems where multiple continuous speech parameters have to be analyzed jointly. A production study on contrastive focus placement in Neapolitan Italian is used as illustration. Two features are analyzed, viz. f0 and relative speech rate, both expressed as(More)
Creating stimuli for perceptual experiments in intonation research involves manipulation of pitch contours extracted from spoken utterances. Difficulties arise when changes in the contour shape need to be applied globally and smoothly in the whole pitch curve. Moreover, it is hard to relate a gradual modification in some contour trait to its perceptual(More)
—In this paper, we face the problem of designing accurate decision-making modules in measurement systems that need to be implemented on resource-constrained platforms. We propose a methodology based on multiobjective optimization and genetic algorithms (GAs) for the analysis of support vector machine (SVM) solutions in the classification error-complexity(More)
In this paper we introduce Functional Data Analysis (FDA) as a tool for analyzing dynamic transitions in speech signals. FDA makes it possible to perform statistical analyses of sets of mathematical functions in the same way as classical multivariate analysis treats scalar measurement data. We illustrate the use of FDA with a reduction phenomenon affecting(More)
Making accurate verbatim transcriptions is very time-consuming and in the case of extemporaneous speech of native and non-native speakers the task is extremely difficult. While previous research focused on evaluating phonemic transcriptions , the goal of our research is the automatic detection of transcription errors on the orthographic level, which degrade(More)
Intonational research is often dependent upon hand-labeling by trained listeners, which can be prone to bias or error. We apply tools from Functional Data Analysis (FDA) to a set of fundamental frequency (F0) data to demonstrate how these tools can provide a less theory-dependent way of investigating F0 contours by allowing statistical analyses of whole(More)
In this study we present a preliminary investigation of the prosodic marking of Verum focus (VF) in Italian, which is said to be realized with a pitch accent on the finite verb (e.g. A: Paul has not eaten the banana-B: (No), Paul HAS eaten the banana!). We tried to discover whether and how Italian speakers prosodically mark VF when producing full-fledged(More)