Preliminary Results of an Intelligibility Measure for English-Speaking Children with Cleft Palate

2007 ◽  
Vol 44 (2) ◽  
pp. 163-174 ◽  
Author(s):  
Megan Hodge ◽  
Carrie L. Gotzke

Objective: This study describes a preliminary evaluation of the construct and concurrent validity of the Speech Intelligibility Probe for Children With Cleft Palate. Design: The study used a prospective between-groups design with convenience samples. Participants: Participants (ages 39 to 82 months) included 5 children with cleft palate and 10 children with typical speech development and no history of craniofacial abnormalities. All children had age-appropriate language skills. Interventions: Each child completed the Speech Intelligibility Probe for Children With Cleft Palate by imitating single words. Each child's word productions were recorded and played back to listeners who completed open-set and closed-set response tasks. Recorded utterances that represented a contiguous 100-word sample of each child's spontaneous speech also were played back to listeners for completion of an open-set word identification task. Main Outcome Measures: Measures reported include group means for (1) intelligibility scores for the open-set Speech Intelligibility Probe for Children With Cleft Palate and spontaneous speech sample conditions, and (2) percentage of phonetic contrasts correct and correct-distorted from the Speech Intelligibility Probe for Children With Cleft Palate closed-set response task. Results: The group of children with cleft palate had significantly lower intelligibility scores, lower percentage of correct phonetic contrasts, and higher percentage of correct distorted items (construct validity). A strong positive correlation (r = .88, p < .01) was found between intelligibility scores from the Speech Intelligibility Probe for Children With Cleft Palate and the spontaneous sample (concurrent validity). Conclusions: The results provide preliminary support for the construct and concurrent validities of the Speech Intelligibility Probe for Children With Cleft Palate as a measure of children's speech intelligibility.

2021 ◽  
Vol 7 ◽  
Author(s):  
Anna Warzybok ◽  
Jan Rennies ◽  
Birger Kollmeier

Masking noise and reverberation strongly influence speech intelligibility and decrease listening comfort. To optimize acoustics for ensuring a comfortable environment, it is crucial to understand the respective contribution of bottom-up signal-driven cues and top-down linguistic-semantic cues to speech recognition in noise and reverberation. Since the relevance of these cues differs across speech test materials and training status of the listeners, we investigate the influence of speech material type on speech recognition in noise, reverberation and combinations of noise and reverberation. We also examine the influence of training on the performance for a subset of measurement conditions. Speech recognition is measured with an open-set, everyday Plomp-type sentence test and compared to the recognition scores for a closed-set Matrix-type test consisting of syntactically fixed and semantically unpredictable sentences (c.f. data by Rennies et al., J. Acoust. Soc. America, 2014, 136, 2642–2653). While both tests yield approximately the same recognition threshold in noise in trained normal-hearing listeners, their performance may differ as a result of cognitive factors, i.e., the closed-set test is more sensitive to training effects while the open-set test is more affected by language familiarity. All experimental data were obtained at a fixed signal-to-noise ratio (SNR) and/or reverberation time set to obtain the desired speech transmission index (STI) values of 0.17, 0.30, and 0.43. respectively, thus linking the data to STI predictions as a measure of pure low-level acoustic effects. The results confirm the consistent difference between robustness to reverberation observed in the literature between the matrix type sentences and the Plomp-type sentences, especially for poor and medium speech intelligibility. The robustness of the closed-set matrix type sentences against reverberation disappeared when listeners had no a priori knowledge about the speech material (sentence structure and words used), thus demonstrating the influence of higher-level lexical-semantic cues in speech recognition. In addition, the consistent difference between reverberation- and noise-induced recognition scores of everyday sentences for medium and high STI conditions and the differences between Matrix-type and Plomp-type sentence scores clearly demonstrate the limited utility of the STI in predicting speech recognition in noise and reverberation.


2020 ◽  
Vol 9 (11) ◽  
pp. 9353-9360
Author(s):  
G. Selvi ◽  
I. Rajasekaran

This paper deals with the concepts of semi generalized closed sets in strong generalized topological spaces such as $sg^{\star \star}_\mu$-closed set, $sg^{\star \star}_\mu$-open set, $g^{\star \star}_\mu$-closed set, $g^{\star \star}_\mu$-open set and studied some of its basic properties included with $sg^{\star \star}_\mu$-continuous maps, $sg^{\star \star}_\mu$-irresolute maps and $T_\frac{1}{2}$-space in strong generalized topological spaces.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Clara Borrelli ◽  
Paolo Bestagini ◽  
Fabio Antonacci ◽  
Augusto Sarti ◽  
Stefano Tubaro

AbstractSeveral methods for synthetic audio speech generation have been developed in the literature through the years. With the great technological advances brought by deep learning, many novel synthetic speech techniques achieving incredible realistic results have been recently proposed. As these methods generate convincing fake human voices, they can be used in a malicious way to negatively impact on today’s society (e.g., people impersonation, fake news spreading, opinion formation). For this reason, the ability of detecting whether a speech recording is synthetic or pristine is becoming an urgent necessity. In this work, we develop a synthetic speech detector. This takes as input an audio recording, extracts a series of hand-crafted features motivated by the speech-processing literature, and classify them in either closed-set or open-set. The proposed detector is validated on a publicly available dataset consisting of 17 synthetic speech generation algorithms ranging from old fashioned vocoders to modern deep learning solutions. Results show that the proposed method outperforms recently proposed detectors in the forensics literature.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adam Goodwin ◽  
Sanket Padmanabhan ◽  
Sanchit Hira ◽  
Margaret Glancey ◽  
Monet Slinowsky ◽  
...  

AbstractWith over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne disease mitigation. Yet this task is hindered by limited global taxonomic expertise and specimen damage consistent across common capture methods. Convolutional neural networks (CNNs) are promising with limited sets of species, but image database requirements restrict practical implementation. Using an image database of 2696 specimens from 67 mosquito species, we address the practical open-set problem with a detection algorithm for novel species. Closed-set classification of 16 known species achieved 97.04 ± 0.87% accuracy independently, and 89.07 ± 5.58% when cascaded with novelty detection. Closed-set classification of 39 species produces a macro F1-score of 86.07 ± 1.81%. This demonstrates an accurate, scalable, and practical computer vision solution to identify wild-caught mosquitoes for implementation in biosurveillance and targeted vector control programs, without the need for extensive image database development for each new target region.


2012 ◽  
Vol 126 (10) ◽  
pp. 989-994 ◽  
Author(s):  
S Hassanzadeh

AbstractObjective:This retrospective study compared the cochlear implantation outcomes of first- and second-generation deaf children.Methods:The study group consisted of seven deaf, cochlear-implanted children with deaf parents. An equal number of deaf children with normal-hearing parents were selected by matched sampling as a reference group. Participants were matched based on onset and severity of deafness, duration of deafness, age at cochlear implantation, duration of cochlear implantation, gender, and cochlear implant model. We used the Persian Auditory Perception Test for the Hearing Impaired, the Speech Intelligibility Rating scale, and the Sentence Imitation Test, in order to measure participants' speech perception, speech production and language development, respectively.Results:Both groups of children showed auditory and speech development. However, the second-generation deaf children (i.e. deaf children of deaf parents) exceeded the cochlear implantation performance of the deaf children with hearing parents.Conclusion:This study confirms that second-generation deaf children exceed deaf children of hearing parents in terms of cochlear implantation performance. Encouraging deaf children to communicate in sign language from a very early age, before cochlear implantation, appears to improve their ability to learn spoken language after cochlear implantation.


Author(s):  
Ragav Sachdeva ◽  
Filipe R. Cordeiro ◽  
Vasileios Belagiannis ◽  
Ian Reid ◽  
Gustavo Carneiro
Keyword(s):  
Open Set ◽  

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Andreas Naros ◽  
Sylva Bartel ◽  
Margit Bacher ◽  
Bernd Koos ◽  
Gunnar Blumenstock ◽  
...  

2021 ◽  
pp. 014272372110422
Author(s):  
Jolien Faes ◽  
Joris Gillis ◽  
Steven Gillis

Auditory brainstem implantation (ABI) is a recent innovation in pediatric hearing restoration in children with a sensorineural hearing impairment. Only limited information is available on the spontaneous speech development of severe-to-profound congenitally hearing-impaired children who received an ABI. The purpose of this study was to investigate longitudinally the accuracy of ABI children’s word productions in spontaneous speech in comparison to the accuracy of children who received a cochlear implant and children with normal hearing. The data of this study consist of recordings of the spontaneous speech of the first three Dutch-speaking children living in Belgium who received an ABI. The children’s utterances were phonemically transcribed and for each word, the distance between the child’s production and the standard adult phonemic transcription was computed using the Levenshtein Distance as a metric. The same procedure was applied to the longitudinal data of the children with CI and the normally hearing children. The main result was that the Levenshtein Distance decreased in the three children with ABI but it remained significantly higher than that of children with typical hearing and cochlear implants matched on chronological age, hearing age, and lexicon size. In other words, the phonemic accuracy increased in the children with ABI but stayed well below that of children without hearing loss and children with cochlear implants. Moreover, the analyses revealed considerable individual variation between the children with ABI.


Author(s):  
Tetiana Osipchuk

The topological properties of classes of generally convex sets in multidimensional real Euclidean space $\mathbb{R}^n$, $n\ge 2$, known as $m$-convex and weakly $m$-convex, $1\le m<n$, are studied in the present work. A set of the space $\mathbb{R}^n$ is called \textbf{\emph{$m$-convex}} if for any point of the complement of the set to the whole space there is an $m$-dimensional plane passing through this point and not intersecting the set. An open set of the space is called \textbf{\emph{weakly $m$-convex}}, if for any point of the boundary of the set there exists an $m$-dimensional plane passing through this point and not intersecting the given set. A closed set of the space is called \textbf{\emph{weakly $m$-convex}} if it is approximated from the outside by a family of open weakly $m$-convex sets. These notions were proposed by Professor Yuri Zelinskii. It is known the topological classification of (weakly) $(n-1)$-convex sets in the space $\mathbb{R}^n$ with smooth boundary. Each such a set is convex, or consists of no more than two unbounded connected components, or is given by the Cartesian product $E^1\times \mathbb{R}^{n-1}$, where $E^1$ is a subset of $\mathbb{R}$. Any open $m$-convex set is obviously weakly $m$-convex. The opposite statement is wrong in general. It is established that there exist open sets in $\mathbb{R}^n$ that are weakly $(n-1)$-convex but not $(n-1)$-convex, and that such sets consist of not less than three connected components. The main results of the work are two theorems. The first of them establishes the fact that for compact weakly $(n-1)$-convex and not $(n-1)$-convex sets in the space $\mathbb{R}^n$, the same lower bound for the number of their connected components is true as in the case of open sets. In particular, the examples of open and closed weakly $(n-1)$-convex and not $(n-1)$-convex sets with three and more connected components are constructed for this purpose. And it is also proved that any compact weakly $m$-convex and not $m$-convex set of the space $\mathbb{R}^n$, $n\ge 2$, $1\le m<n$, can be approximated from the outside by a family of open weakly $m$-convex and not $m$-convex sets with the same number of connected components as the closed set has. The second theorem establishes the existence of weakly $m$-convex and not $m$-convex domains, $1\le m<n-1$, $n\ge 3$, in the spaces $\mathbb{R}^n$. First, examples of weakly $1$-convex and not $1$-convex domains $E^p\subset\mathbb{R}^p$ for any $p\ge3$, are constructed. Then, it is proved that the domain $E^p\times\mathbb{R}^{m-1}\subset\mathbb{R}^n$, $n\ge 3$, $1\le m<n-1$, is weakly $m$-convex and not $m$-convex.


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