Speaker Age Research Articles

UEG Training Support - a good option to finance your high quality postgraduate teaching!

United European Gastroenterology is a successful federation of gastroenterological societies (called member societies). Thanks to its organizational success it may allocate as much as half a million Euro to support postgraduate teaching in gastroenterology in Europe. Every gastroenterological society that is a member of UEG (16 specialist societies “Ordinary Members” and 46 national societies “National Society Members”) may apply. This is a great opportunity! Two main forms of postgraduate teaching are supported. One is the support of a single regular educational meeting (up to 25,000 euro may be granted). Second is the support of a long-term educational project planned for three consecutive years with the intention to develop stand-alone long-term educational event. In this type of event, the first year is granted with up to € 50,000 and the subsequent two years with up to €25,000 euro each year. For the last two years a specially designed scoring system to evaluate applications is in place. It promotes several aspects of teaching that are regarded by UEG to be very important. Namely, the high scores are applied for such aspects like interactivity and multidisciplinarity. Therefore we check whether organizers allowed enough time for discussion, whether they are planning to use voting interactive system or include in the programme case presentation with participation of the audience in solving clinical problems. We also look at such aspects as balance in geographical distribution of speakers and attendees, age and gender of speakers, location of the postgraduate course and planned cooperation with other society. Of course, the typical and obvious criteria are also applied as justification of undertaking the course, the topic of the course, well-structured budget etc. Well visible is also such preparation of the course that the materials (e.g. recordings) may be used by the UEG e-learning platform. All applications are scored by the members of the Educational Committee that consists of one representative from each Ordinary Member Society of UEG. Of course, members are excluded from judging their own society application. The system of voting and democratic methodology is regarded as fair and valuable. For example the number of applications per society as well as number of granted support per society is not limited. So, if there are many good proposals from a given society they all could be granted. In order to keep the high standards it was decided that the score below the 50% of attainable scoring will not be considered for support. Of course, nothing is ideal; but we think that such evaluation system is better than the old, opinion-based system. Results of the last two years application process are presented in Table 1. There are several criteria that have to be fulfilled not only during application process but also during and after the education event. Examples are: a need to place a logo of UEG at all event materials and the event website, or a need to submit a report after the meeting has taken place. These points and others are required and if not fulfilled the grant will not be paid. Details for those who want to place application may be found at www.ueg.eu/education/ts/. This year application is open from February 17 until May 12 for 2015 events. We invite all gastroenterological societies to try. We want to sponsor the best education in gastroenterology.

The merged vowel of PIN and PEN as realized in Bakersfield, California

One consistently identified quality of Southern American English (SAE) is the PIN/PEN merger, wherein the vowels /ɪ/ and /ɛ/ become indistinguishable in nasalized contexts. Existing studies have shown that the merged vowel may either occupy a space between the vowel spaces of /ɪ/ and /ɛ/ [Bigham, MA thesis, UT Austin (2005)], or merge completely into /ɪ/[Koops et al., “The effect of perceived speaker age on the perception of PIN and PEN vowels in Houston, Texas,” U Penn Working Pap. Linguist. 14(2) (2008)]. Due to the dustbowl migration, areas of the southern central valley of California have a complete PIN/PEN merger similar to SAE. This study examines the acoustic properties of the merged vowel spoken by eight speakers from Bakersfield, California, ages 25 through 65. Findings indicate that the merged vowel does not occupy a compromise position, nor a merged /ɪ/ position in any but the oldest subject. Instead, the merged vowel presents significantly lower first formant values than /ɪ/, suggesting that as the California vowel shift has lowered the front lax vowels, this merged allophone has remained stationary. Further, the youngest female subjects presented an inconsistent vowel merger, suggesting a potential demerger of the type documented in southern urban centers. This raises questions about the nature of the alleged merger, if perceptible acoustic differences remain which allow for demerger.

Language and an expression of identities: Japanese sentence-final particles ne and na

This study explores the interrelationship between language and the biographical characteristics of the speaker, including gender, age and social status, by examining the interactional functions of two Japanese sentence-final particles ne and na. A major claim in the literature is that although these particles share some similar functions, they differ markedly in terms of gender, age and social status of the speaker: for example, na is used by male speakers only while ne does not have such a restriction. To date, however, little research has systematically examined their differences, and consequently the use of na including its connection with the speaker's gender, age and social status has also been neglected. This study provides a comprehensive analysis of the functions of ne and na by exploring not only their similarities, but also their differences, and sheds light on some aspects of the nature of the identity-language interface. The study will claim that the use of na does not directly indicate the speaker's biographical characteristics. Rather, its special tone of ‘camaraderie’ is closely linked to sociocultural values on gender and formality in the Japanese language, and consequently its use manifests the particular gender, age and social status of the speaker.

The functions of еру modal verb «should» in the corpus ice-gb

The article adresses the modal and grammatical functions of the polyfunctional verb should as presented in the language corpus ICE-GB compiled in 1993. It is based on the ideas of poly functionalism laid out in the works of A. Smirnitsky, T. Komova, and others scientists. The author aims at studying the distribution of functions of the verb should; the material is also considered from the standpoint of the extralinguistic parameters of the speaker's gender and age. The analysis of the material shows that the modal function still prevails over the grammatical one, which explains the logic of presenting the material in books on grammar where the first meaning of this verb to be studied is (mild) obligation. The grammatical function is realized in the Suppositional and Conditional oblique moods (A. Smirnitsky's classification). Genderwise, men's speech contains a few more polite formulae that show more consideration for the interlocutor which is generally considered to be typical of women's speech; on the other hand, there is some proof that phrases constructed by men are perceived as more aggressive. Bringing the speaker's age into play seems to suggest that a higher ratio of oblique moods in the speech signifies a free use of language. Some of the notional lexical verbs forming regular collocations with should have been singled out and grouped.

Effects of Phonological Neighborhood Density on Accuracy of Picture Naming in Aphasia

Effects of Phonological Neighborhood Density on Accuracy of Picture Naming in Aphasia

Further Evidence for Arabic Basic Colour Categories

The aim of this study was to describe the basic colour terms (BCTs) of Arabic and, in particular, clarify the relationship among the three Arabic terms for blue: azrock, samawee, and khuhlie that suggested a BCTs in Arabic language in Al-rasheed et al. (2013). Data were collected from adult native Arabic speakers (30 male and 27 female) age between 18 and 34 years old, with a mean age of 21.67 years (SD = 2.98). All were under and postgraduate students at King Saud University. Participants task was to group the 320 colours by similarity. Based on this result, Arabic probably has eleven basic colour terms and these correspond with Berlin and Kay’s eleven universal categories. The terms are that ahmar “red”, akhdar “green”, asfer, “yellow”, azrock “blue”, asswed “black”, abiyadh “white”, banafsagee “purple”, boartoogaalee “orange”, bonee “brown”, wardee “pink” and rassasee. In addition, the terms of particular interest—samawee (“light blue”) had the next highest claim to being basic and may deserve further investigating.

Synchronic variation in the expression of French negation: A Distributed Morphology approach

ABSTRACTThis article discussesne-variation in French sentential negation based on the phonologically transcribed corpus T-zéro (cf. Meisner, in preparation) which allows a new interpretation of the facts. In the last decades, sociolinguistic and stylistic approaches to linguistic variation in French (cf. Armstrong, 2001) have shown that extra-linguistic factors, such as the speaker's age, sex, social background or geographic origin as well as the communication situation may have considerable influence on variablene-omission. However, in contrast to most sociolinguistic studies dedicated to this phenomenon (cf. Ashby, 1976, 1981, 2001; Armstrong and Smith, 2002; Coveney, 2002) we will focus on the linguistic factors influencingne-variation, since their importance is empirically evident but not yet fully exploited on a theoretical level.One leading assumption with respect tone-variation in literature is that the particleneis most frequently retained in combination with a proper name or a full DP and is commonly omitted when combined with clitic subjects. However, there are many exceptions to this rule which, as we argue, can be better explained by considering the phonological form of the involved subject.Ne-realisation is treated here as an inner-grammatical phenomenon that is triggered by context sensitivity with regard to the element to its left, i.e. usually the grammatical subject, and not as a consequence of ‘code-switching’ between two grammars nor as a sociolinguistic variable characterising certain groups of speakers in the Labovian sense (cf. Labov, 1972), since we seek to describe general variational tendencies, present in nearly all speakers of contemporary European French. Our analysis, which is implemented in a Distributed Morphology framework (Halle & Marantz, 1994), is compatible, however, with stylistic approaches tone-variation, such as audience design (cf. Bell, 1984, 2001).

Modeling the perception of speaker age and sex in children's voices

At previous meetings, we presented data on the perception of speaker sex and age in children's voices. The stimuli common to these experiments were /hVd/ syllables in isolation and sentence context. Here we present the results of a modeling study in which acoustic measurements of the /hVd/ syllables were used to predict listener judgments of age and sex. Variables were selected based on preliminary analyses and suggestions from the literature: (1) duration; (2) average fundamental frequency; (3) geometric mean of F1 F2 F3; (4) magnitude difference between harmonics 1 and 2; (5) magnitude difference between harmonic 1 and F3 peak; (6) Cepstral pitch prominence; (7) Harmonic-to-noise ratio. Logistic regression models were constructed to predict listeners' judgments of speaker sex, and mixed effects linear regression models for speaker age. Results confirmed the importance of F0, formant frequencies and measures related to the voicing source for both age and sex. Regression coefficients for judgments of age and sex were similar to those for veridical age and sex when regressed on the same physical measures, suggesting a near-optimal use of cues by listeners.

Spanish variable direct object marking

In studying the social conditioning of Differential Object Marking (DOM) in Spanish we show a social dimension underlying the variable use of DOM: age of speakers has a moderate but significant effect, with middle-aged speakers showing an increase in overt marking. Previously, the implicit consensus was that there is no sociolectal variation in DOM. To ensure the statistical validity of our results, we developed an original, rigorous, quantitative approach to correct for the unbalanced distribution of the data across factor groups. A problem that has been frequently mentioned in the specialized literature, but never satisfactorily resolved for the linguistic analysis of corpus data.

Perception of speaker age in children’s voices

To study the perception of speaker age in children’s voices, adult listeners were presented with vowels in /hVd/ syllables either in isolation or in a carrier sentence, and used a graphical slider to register their estimate of the speaker’s age. The data showed a moderate correlation of perceived age and chronological age. Age estimation accuracy was fairly constant across age up to about age 11, but there was a systematic tendency for listeners to underestimate the ages of older girls. This tendency was actually enhanced when listeners were informed of the speaker’s sex. Age estimation accuracy was higher for syllables embedded in a carrier sentence. Linear regression analyses were conducted using acoustic measurements of the stimuli to predict perceived age. These analyses indicated significant contributions of fundamental frequency, duration, vowel category, formant frequencies, as well as certain measures related to the voicing source. The persistent underestimation of age for older girls, and the effect knowledge of speaker sex has on this underestimation suggest that acoustic information is combined with expectations regarding speakers of a given sex in arriving at an estimate of speaker age.

Tracking reading: dual task costs of oral reading for young versus older adults.

A digital pursuit rotor was used to monitor oral reading costs by time-locking tracking performance to the auditory wave form produced as young and older adults were reading out short paragraphs. Multilevel modeling was used to determine how paragraph-level predictors of length, grammatical complexity, and readability and person-level predictors such as speaker age or working memory capacity predicted reading and tracking performance. In addition, sentence-by-sentence variation in tracking performance was examined during the production of individual sentences and during the pauses before upcoming sentences. The results suggest that dual tasking has a greater impact on older adults' reading comprehension and tracking performance. At the level of individual sentences, young and older adults adopt different strategies to deal with grammatically complex and propositionally dense sentences.

Intelligibility of Children’s Speech in Digitized Speech

The current investigation examined the intelligibility of digitized speech recorded from typically developing child speakers, ages 4, 5, 6, and 7 years, and reproduced on an augmentative and alternative communication (AAC) device with digitized speech output. The study used a between group design. Forty adults were asked to transcribe 120 words spoken by child speakers in one of the age groups, and presented on an AAC device with digitized speech output. The dependent variable was intelligibility (percent of words correctly identified) of the children’s speech. Overall, the intelligibility of children’s speech increases with the age of the child speaker. However, there was a lot of individual variation in the intelligibility of children’s voices. There was no clear cut-off age, although the speech of some young children may not be sufficiently intelligible on an AAC device that uses digitized speech. Clinicians and parents choosing child speakers for AAC devices with digitized speech are cautioned to carefully consider the speakers used for recording digitized speech output and the characteristics of the speech of the individual speaker. Future research directions are discussed.

Emerging Adulthood in Sociolinguistics

Emerging Adulthood in Sociolinguistics

Automatic speaker age and gender recognition using acoustic and prosodic level information fusion

The paper presents a novel automatic speaker age and gender identification approach which combines seven different methods at both acoustic and prosodic levels to improve the baseline performance. The three baseline subsystems are (1) Gaussian mixture model (GMM) based on mel-frequency cepstral coefficient (MFCC) features, (2) Support vector machine (SVM) based on GMM mean supervectors and (3) SVM based on 450-dimensional utterance level features including acoustic, prosodic and voice quality information. In addition, we propose four subsystems: (1) SVM based on UBM weight posterior probability supervectors using the Bhattacharyya probability product kernel, (2) Sparse representation based on UBM weight posterior probability supervectors, (3) SVM based on GMM maximum likelihood linear regression (MLLR) matrix supervectors and (4) SVM based on the polynomial expansion coefficients of the syllable level prosodic feature contours in voiced speech segments. Contours of pitch, time domain energy, frequency domain harmonic structure energy and formant for each syllable (segmented using energy information in the voiced speech segment) are considered for analysis in subsystem (4). The proposed four subsystems have been demonstrated to be effective and able to achieve competitive results in classifying different age and gender groups. To further improve the overall classification performance, weighted summation based fusion of these seven subsystems at the score level is demonstrated. Experiment results are reported on the development and test set of the 2010 Interspeech Paralinguistic Challenge aGender database. Compared to the SVM baseline system (3), which is the baseline system suggested by the challenge committee, the proposed fusion system achieves 5.6% absolute improvement in unweighted accuracy for the age task and 4.2% for the gender task on the development set. On the final test set, we obtain 3.1% and 3.8% absolute improvement, respectively.

Emotion and mental state recognition from speech

As research in speech processing has matured, attention has gradually shifted from linguistic-related applications such as speech recognition towards paralinguistic speech processing problems, in particular the recognition of speaker identity, language, emotion, gender, and age. Determination of a speaker’s emotion or mental state is a particularly challenging problem, in view of the significant variability in its expression posed by linguistic, contextual, and speaker-specific characteristics within speech. In response, a range of signal processing and pattern recognition methods have been developed in recent years. Recognition of emotion and mental state from speech is a fundamentally multidisciplinary field, comprising contributions from psychology, speech science, linguistics, (cooccurring) nonverbal communication, machine learning, artificial intelligence and signal processing, among others. Some of the key research problems addressed to date include isolating sources of emotion-specific information in the speech signal, extracting suitable features, forming reduced-dimension feature sets, developing machine learning methods applicable to the task, reducing feature variability due to speaker and linguistic content, comparing and evaluating diverse methods, robustness, and constructing suitable databases. Studies examining the relationships between the psychological basis of emotion, the effect of emotion on speech production, and the measurable differences in the speech signal due to emotion have helped to shed light on these problems; however, substantial research is still required. Taking a broader view of emotion as a mental state, signal processing researchers have also explored the possibilities of automatically detecting other types of mental state which share some characteristics with emotion, for example stress, depression, cognitive load, and ‘cognitive epistemic’ states such as interest, scepticism, etc. The recent interest in emotion recognition research has seen applications in call centre analytics, human-machine and humanrobot interfaces, multimedia retrieval, surveillance tasks, behavioural health informatics, and improved speech recognition. This special issue comprises nine articles covering a range of topics in signal processing methods for vocal source and acoustic feature extraction, robustness issues, novel applications of pattern recognition techniques, methods for detecting mental states and recognition of non-prototypical spontaneous and naturalistic emotion in speech. These articles were accepted following peer review, and each submission was handled by an editor who was independent from all authors listed in that manuscript. Herein, we briefly introduce the articles comprising this special issue. Trevino, Quatieri and Malyska bring a new level of sophistication to an old problem, detecting signs of depressive disorders in speech. Their measures of depression come from standard psychiatric instruments, Quick Inventory of Depressive Symptomatology and Hamilton Depression rating scales. These are linked to measures of speech timing that are much richer than the traditional global measures of speech rate. Results indicate that different speech sounds and sound types behave differently in depression, and may relate to different aspects of depression. Caponetti, Buscicchio and Castellano propose the use of a more detailed auditory model than that embodied in the widely employed mel frequency cepstral coefficients, for extracting detailed spectral features during emotion recognition. Working from the Lyon cochlear model, the authors demonstrate improvements on a five-class problem from the speech under simulated and actual stress database. Their study also further validates the applicability of long short-term memory recurrent neural networks for classification in emotion and mental state recognition problems. Callejas, Griol and Lopez-Cozar propose a mental state prediction approach that considers both speaker * Correspondence: j.epps@unsw.edu.au School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW 2052, Australia Full list of author information is available at the end of the article Epps et al. EURASIP Journal on Advances in Signal Processing 2012, 2012:15 http://asp.eurasipjournals.com/content/2012/1/15

Effect of Speaker Age on Speech Recognition and Perceived Listening Effort in Older Adults With Hearing Loss

Older adults exhibit difficulty understanding speech that has been experimentally degraded. Age-related changes to the speech mechanism lead to natural degradations in signal quality. We tested the hypothesis that older adults with hearing loss would exhibit declines in speech recognition when listening to the speech of older adults, compared with the speech of younger adults, and would report greater amounts of listening effort in this task. Nineteen individuals with age-related hearing loss completed speech recognition and listening effort scaling tasks. Both were conducted in quiet, when listening to high- and low-predictability phrases produced by younger and older speakers, respectively. No significant difference in speech recognition existed when stimuli were derived from younger or older speakers. However, perceived effort was significantly higher when listening to speech from older adults, as compared with younger adults. For older individuals with hearing loss, natural degradations in signal quality may require greater listening effort. However, they do not interfere with speech recognition-at least in quiet. Follow-up investigation of the effect of speaker age on speech recognition and listening effort under more challenging noise conditions appears warranted.

Speaker age detection using eigen value

In this research an algorithm was suggested for classifying a speaker age to two classes: (young and old classes) based on his speech signal. The suggested algorithm depend on a speech signal feature extraction in order to get a compact representation for this signal and to adopte these features in the classification process. In this algorithm, the eigen values of the covariance matrix was adopted as a principle parameter in the recognition between the two classes. It was constructed from the data of the speech signal (usually one dimension( after rearranghng it into a number (2,4,8,16,32,64) of a two dimension square matrix array . The suggested algorithm include two main stages: • 1st stage: includes data file preparation that contains the eigen values for a number of persons belong to both classes young and old (with different gender), in this stage the average of these values for each class to be calculated separately and the threshold curve(which represents the boundary seperating between two classes( were also computed. Second stage: in this stage the classification process was done by comparing the curve that represents the eigen values of the speech signal, with the threshold curve, a different number of performance parameters are adopted in the evaluation the accuracy of the classification process. The measured correlation value was in range of (0.9610, 0.9994) when m=2 and m=64, respectively (this means whenever the number of arrays that the speech signal constructed from it increases, the correlation coefficient also increases) , while a clear difference can be seen with mmse parameter. After applying the suggested algorithm on 50 persons from both genders, the algorithm passed in applying 80% and failed in percentage 20% of them.

Cortical correlates of self-generation in verbal paired associate learning

Behavioral studies have shown that verbal information is better retained when it is self-generated rather than read (learned passively). We used fMRI and a paired associates task to examine brain networks underlying self-generated memory encoding. Subjects were 49 healthy English speakers ages 19–62 (30 female). In the fMRI task, related word pairs were presented in a “read” condition, where subjects viewed both words and read the second word aloud, or a “generate” condition, where the second word was presented with only the first letter and the subject was required to generate the word. Thirty word pairs were presented in each condition. After the fMRI scan, words that were read or generated were presented, each with two foils, in a forced-choice recognition task. On the recognition post-test, words from the “generate” condition were more correctly recognized than from the “read” condition (80.0% for generated words versus 72.0% for read words; t(48)=5.17, p<0.001). FMRI revealed increased activation for generate>read in inferior/middle frontal gyri bilaterally (L>R), anterior cingulate, and caudate nucleus and the temporo-parietal–occipital junction bilaterally. For the “read” condition, better subsequent memory performance across individual subjects was positively correlated with activation in the cuneus bilaterally. In the “generate” condition, better subsequent memory performance was positively correlated with activation in the left superior temporal gyrus. These results suggest that self-generation improves memory performance, that enhanced cortical activation accompanies self-generated encoding, and that recruitment of a specific brain network underlies self-generated encoding. The findings may have implications for the development of procedures to enhance memory performance.

Supervector Dimension Reduction for Efficient Speaker Age Estimation Based on the Acoustic Speech Signal

This paper presents a novel dimension reduction method which aims to improve the accuracy and the efficiency of speaker's age estimation systems based on speech signal. Two different age estimation approaches were studied and implemented; the first, age-group classification, and the second, precise age estimation using regression. These two approaches use the Gaussian mixture model (GMM) supervectors as features for a support vector machine (SVM) model. When a radial basis function (RBF) kernel is used, the accuracy is improved compared to using a linear kernel; however, the computation complexity is more sensitive to the feature dimension. Classic dimension reduction methods like principal component analysis (PCA) and linear discriminant analysis (LDA) tend to eliminate the relevant feature information and cannot always be applied without damaging the model's accuracy. In our study, a novel dimension reduction method was developed, the weighted-pairwise principal components analysis (WPPCA) based on the nuisance attribute projection (NAP) technique. This method projects the supervectors to a reduced space where the redundant within-class pairwise variability is eliminated. This method was applied and compared to the baseline system where no dimensionality reduction is done on the supervectors. The conducted experiments showed a dramatic speed-up in the SVM training testing time using reduced feature vectors. The system accuracy was improved by 5% for the classification system and by 10% for the regression system using the proposed dimension reduction method.

Spatial frames of reference in Seri

This paper describes spatial frames of reference (FoRs) preferences among speakers of Seri, a language isolate of Sonora, Mexico. Seri speakers have various options when it comes to FoR selection in discourse, but tend to favor object-centered and direct FoRs. There is also noticeable speaker variation in terms of FoR preferences, especially as it pertains to landmark-based FoRs, which are favored by only some speakers, and the scarce use of absolute FoRs, which seems to be determined by speaker age.