An acoustic investigation of the developmental trajectory of lexical stress contrastivity in Italian

We examined whether typically developing Italian children exhibit adult-like stress contrastivity for word productions elicited via a picture naming task (n=25 children aged 3\u20135 years and 27 adults). Stimuli were 10 trisyllabic Italian words; half began with a weak\u2013strong (WS) pattern of lexical stress across the initial 2 syllables, as in patata, while the other half began with a strong\u2013weak (SW) pattern, as in gomito. Word productions that were identified as correct via perceptual judgement were analysed acoustically. The initial 2 syllables of each correct word production were analysed in terms of the duration, peak intensity, and peak fundamental frequency of the vowels using a relative measure of contrast\u2014the normalised pairwise variability index (PVI). Results across the majority of measures showed that children\u2019s stress contrastivity was adult-like. However, the data revealed that children\u2019s contrastivity for trisyllabic words beginning with a WS pattern was not adult-like regarding the PVI for vowel duration: children showed less contrastivity than adults. This effect appeared to be driven by differences in word-medial gemination between children and adults. Results are compared with data from a recent acoustic study of stress contrastivity in English speaking children and adults and discussed in relation to language-specific and physiological motor-speech constraints on production

Text Preprocessing for Speech Synthesis

In this paper we describe our text preprocessing modules for English text-to-speech synthesis. These modules comprise rule-based text normalization subsuming sentence segmentation and normalization of non-standard words, statistical part-of-speech tagging, and statistical syllabification, grapheme-to-phoneme conversion, and word stress assignment relying in parts on rule-based morphological analysis

Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. In this study acoustic measures of speech in conjunction with voxel-based morphometry were used to determine the success of the measures as an adjunct to diagnosis and to explore the neural basis of apraxia of speech in nfvPPA. Forty-one patients (21 lvPPA, 20 nfvPPA) were recruited from a consecutive sample with suspected frontotemporal dementia. Patients were diagnosed using the current gold-standard of expert perceptual judgment, based on presence/absence of particular speech features during speaking tasks. Seventeen healthy age-matched adults served as controls. MRI scans were available for 11 control and 37 PPA cases; 23 of the PPA cases underwent amyloid ligand PET imaging. Measures, corresponding to perceptual features of apraxia of speech, were periods of silence during reading and relative vowel duration and intensity in polysyllable word repetition. Discriminant function analyses revealed that a measure of relative vowel duration differentiated nfvPPA cases from both control and lvPPA cases (r2 = 0.47) with 88% agreement with expert judgment of presence of apraxia of speech in nfvPPA cases. VBM analysis showed that relative vowel duration covaried with grey matter intensity in areas critical for speech motor planning and programming: precentral gyrus, supplementary motor area and inferior frontal gyrus bilaterally, only affected in the nfvPPA group. This bilateral involvement of frontal speech networks in nfvPPA potentially affects access to compensatory mechanisms involving right hemisphere homologues. Measures of silences during reading also discriminated the PPA and control groups, but did not increase predictive accuracy. Findings suggest that a measure of relative vowel duration from of a polysyllable word repetition task may be sufficient for detecting most cases of apraxia of speech and distinguishing between nfvPPA and lvPPA

A Comparison of Feature-Based and Neural Scansion of Poetry

Automatic analysis of poetic rhythm is a challenging task that involves linguistics, literature, and computer science. When the language to be analyzed is known, rule-based systems or data-driven methods can be used. In this paper, we analyze poetic rhythm in English and Spanish. We show that the representations of data learned from character-based neural models are more informative than the ones from hand-crafted features, and that a Bi-LSTM+CRF-model produces state-of-the art accuracy on scansion of poetry in two languages. Results also show that the information about whole word structure, and not just independent syllables, is highly informative for performing scansion.Comment: RANLP 201

Linguistic Optimization

Optimality Theory (OT) is a model of language that combines aspects of generative and connectionist linguistics. It is unique in the field in its use of a rank ordering on constraints, which is used to formalize optimization, the choice of the best of a set of potential linguistic forms. We show that phenomena argued to require ranking fall out equally from the form of optimization in OT's predecessor Harmonic Grammar (HG), which uses numerical weights to encode the relative strength of constraints. We further argue that the known problems for HG can be resolved by adopting assumptions about the nature of constraints that have precedents both in OT and elsewhere in computational and generative linguistics. This leads to a formal proof that if the range of each constraint is a bounded number of violations, HG generates a finite number of languages. This is nontrivial, since the set of possible weights for each constraint is nondenumerably infinite. We also briefly review some advantages of HG

Pauses and the temporal structure of speech

Natural-sounding speech synthesis requires close control over the temporal structure of the speech flow. This includes a full predictive scheme for the durational structure and in particuliar the prolongation of final syllables of lexemes as well as for the pausal structure in the utterance. In this chapter, a description of the temporal structure and the summary of the numerous factors that modify it are presented. In the second part, predictive schemes for the temporal structure of speech ("performance structures") are introduced, and their potential for characterising the overall prosodic structure of speech is demonstrated

Lexicality and frequency in specific language impairment: accuracy and error data from two nonword repetition tests

Purpose: Deficits in phonological working memory and deficits in phonological processing have both been considered potential explanatory factors in Specific Language Impairment (SLI). Manipulations of the lexicality and phonotactic frequency of nonwords enable contrasting predictions to be derived from these hypotheses. Method: 18 typically developing (TD) children and 18 children with SLI completed an assessment battery that included tests of language ability, non-verbal intelligence, and two nonword repetition tests that varied in lexicality and frequency. Results: Repetition accuracy showed that children with SLI were unimpaired for short and simple high lexicality nonwords, whereas clear impairments were shown for all low lexicality nonwords. For low lexicality nonwords, greater repetition accuracy was seen for nonwords constructed from high over low frequency phoneme sequences. Children with SLI made the same proportion of errors that substituted a nonsense syllable for a lexical item as TD children, and this was stable across nonword length. Conclusions: The data show support for a phonological processing deficit in children with SLI, where long-term lexical and sub-lexical phonological knowledge mediate the interpretation of nonwords. However, the data also suggest that while phonological processing may provide a key explanation of SLI, a full account is likely to be multi-faceted

Stochastic phonological grammars and acceptability

In foundational works of generative phonology it is claimed that subjects can reliably discriminate between possible but non-occurring words and words that could not be English. In this paper we examine the use of a probabilistic phonological parser for words to model experimentally-obtained judgements of the acceptability of a set of nonsense words. We compared various methods of scoring the goodness of the parse as a predictor of acceptability. We found that the probability of the worst part is not the best score of acceptability, indicating that classical generative phonology and Optimality Theory miss an important fact, as these approaches do not recognise a mechanism by which the frequency of well-formed parts may ameliorate the unacceptability of low-frequency parts. We argue that probabilistic generative grammars are demonstrably a more psychologically realistic model of phonological competence than standard generative phonology or Optimality Theory.Comment: compressed postscript, 8 pages, 1 figur