Voice Of Speaker Research Articles

The Last Island by Zülfü Livaneli

Reviewed by: The Last Island by Zülfü Livaneli Matt A. Hanson Zülfü Livaneli The Last Island Trans. Ayşe A. Şahin. New York. Other Press. 2022. 320 pages. ABOUT A QUARTER of the way through The Last Island, Zülfü Livaneli's latest novel to be translated into English, a figure known as "the President" cannot sleep at night. His title bears an uncanny resemblance to plutocratic heads of state from the US, or Turkey, people so reviled they've shed their names and humanness. Livaneli's "President" hears what sounds like a man on his private terrace. He is convinced that it is a break-in. After succumbing to the truth that it was a seagull, he wages war on the birds. Any enemy will do, ideally the weak and innocent. In 2008, when Livaneli wrote his tenth book, The Last Island, he did not know how much the metaphorical import of his novel would appreciate. It first became timely five years later, when the Gezi Park protests started in the spring of 2013, rallying an unprecedented millions of Turkish citizens to exercise their right to free assembly through acts of civil disobedience and revolutionary fervor, initially to protect the environmental integrity of Istanbul's core. He is like "the Writer" of his allegorical tale, The Last Island, because his oppositional writing is prescient. Due in no small part to Gezi's conservative backlash, Turkey's dictatorial strongman rule has since amassed power unlike any regime in the history of the Turkish republic, stoking fear as its centennial coincides with elections in 2023. Livaneli's aging reputation as a dissident crooner and secular leftist continues with his novelization of liberal democratic values. His letters will likely be kept within that precious, endangered field in Turkey, where creative inquiry feeds humanitarian witnessing to effect lasting sociopolitical change. But, to the chagrin of readers and many of his sorely untranslated fellow novelists in Turkey, Livaneli's fiction does not express the spitfire and grit that roils up from the bloody soil of Anatolia's territorial memory, its popular, multigenerational traumas overheating in the wake of mass suppression and arbitrary arrest. Whereas so much of modern Turkish literature brews with rugged, intoxicating force in the face of state terror, Livaneli's pages are soft, tearful cries of melodrama that ultimately read like the vague prognosis of a bumbling country doctor. In the midst of Turkey's pantheon of imprisoned social novelists like Ahmet Altan, Sevgi Soysal, or Yashar Kemal, the fact that Livaneli served multiple prison sentences for his activism does not vindicate his often flaccid and stereotypical lines. His abject failure to craft thoughtful and convincing novelistic prose is not the fault of his admirable translators, Brendan Freely, and in the case of The Last Island, Ayşe Şahin, who should be lauded for their underestimated labor, globalizing Turkish storytelling while its authors lose their languages and livelihoods. At the opening of The Last Island, Livaneli makes an honest confession. In his characteristic voice on the page, a relatively flat, overemotional being of detached omnipresence, he says that he is not a writer. Or, more accurately, he is not the best writer for his narrative, because that person has been silenced. In the stead of the lost, his is the last voice speaking. But, beyond his book, it is presumptuous to the point of eye-rolling megalomania to obscure the undying and proud struggle of Turkish writers who still work in and out of jail and exile. In the long and fruitful tradition of employing the island as a literary device, Livaneli is following in the footsteps of Aldous Huxley, William Golding, and others. But he shamelessly and shallowly drops names, referring to historical luminaries like Rousseau, Freud, and Voltaire. His novel reads more like the text of a man vainly trying to write than that of a genuine attempt at contemporary literature. Livaneli, it seems, is writing because he can while others cannot. He feels indebted to his compatriots, allied to the struggle of moral uprightness. Turkish American novelist Elif Batuman touched the essence of Western literature's dual nature with her recently published second novel, Either/Or...

Efficient Personalized Speech Enhancement Through Self-Supervised Learning

This work presents self-supervised learning methods for monaural speaker-specific (i.e., personalized) speech enhancement models. While general-purpose models must broadly address many speakers, personalized models can adapt to a particular speaker's voice, expecting to solve a narrower problem. Hence, personalization can achieve more optimal performance in addition to reducing computational complexity. However, naive personalization methods can inconveniently require clean speech from the target user, e.g., due to subpar recording conditions. To this end, we pose personalization as either a zero-shot task, in which no clean speech of the target speaker is used, or a few-shot learning task, which is to minimize the duration of the clean speech used for transfer learning. With this paper, we propose self-supervised learning methods as a solution to both zero- and few-shot personalization tasks. The proposed methods learn the personalized speech features from unlabeled data (i.e., in-the-wild noisy recordings from the target user) rather than from the clean sources. We investigate three different self-supervised learning mechanisms. We set up a pseudo speech enhancement problem as a pretext task, which pretrains the models to estimate noisy speech as if it were the clean target. Contrastive learning and data purification methods regularize the loss function of the pseudo enhancement problem, overcoming the limitations of learning from unlabeled data. We assess our methods by personalizing the well-known ConvTasNet architecture to twenty different target speakers. The results show that self-supervision-based personalization improves the original ConvTasNet's enhancement quality with fewer model parameters and less clean data from the target user.

SPEECH EMOTION RECOGNITION

Speech Emotion Recognition, abbreviated as SER, is the act of attempting to recognize human emotion and affective states from speech. This is capitalizing on the fact that voice often reflects underlying emotion through tone and pitch. This is also the phenomenon that animals like dogs and horses employ to be able to understand human emotion. SER is tough because emotions are subjective and annotating audio is challenging.The main objective of this SER, recognizing the emotional state of the speaker from his/her speaker. Various emotions like happiness, sadness, anger, etc. can be recognized. SER uses speech processing to recognize the emotional state. Speech Processing is one of the important branches of digital signal processing and finds applications in Humancomputer interfaces, Telecommunication, Assistive technologies, Audio mining, Security, and so on. Speech Emotion Recognition is important to have a natural interaction between human beings and machines. In SER, the emotional state of a speaker is extracted from his/her speech. The acoustic characteristic of the speech signal is Feature. Feature extraction is the process that extracts a small amount of data from the speech signal that can later be used to represent each speaker. Many feature extraction methods are available and Mel Frequency Cepstral Coefficient (MFCC) is the commonly used method. In this project, speaker emotions are recognized using the data extracted from the speaker's voice signal. Mel Frequency Cepstral Coefficient (MFCC) technique is used to recognize the emotion of a speaker from their voice.

Social Media Poetics: The Technological Forms of Alt Lit Poetry

Social Media Poetics:The Technological Forms of Alt Lit Poetry Justin Tonra (bio) "140+140!" was the tweet that heralded a defining change to Twitter. On November 7, 2017, Twitter founder JACK DORSEY announced that the maximum length of a tweet would be increased to 280 characters from its previous limit of 140. The change was intended to remove a constraint that was perceived to hinder expression, leading to abandoned tweets among English language users.1 For a business model based on the aggregation of data for the purposes of advertising and data licensing, abandoned tweets represented unrealized commercial potential. However, for poets who had used Twitter's 140-character constraint to draft and publish lines of verse, the change was not so profitable. In the last decade, social media has proved an unexpectedly rich breeding ground for certain poets to publish and promote their poetry. Rupi Kaur has primarily used Instagram to share her poetry, selling more than eleven million copies of her books since her self-published debut, milk and honey (2014). With other poets achieving fame and commercial success on other platforms, the phenomenon of social media poetry has resulted in a dizzying blend of egalitarian publishing opportunity, canny marketing, and an assemblage of "scammers and opportunists and ironists."2 However, many writers from the Alt Lit movement have also used social [End Page 597] media platforms as catalysts for creative inspiration and formal experiment. This movement, whose heyday was the first half of the 2010s, was characterized by online- and self-publication and by its authors' relentless social media activity. Primarily an online community, its leading contributors made successful transitions to print with major publishers. Alt Lit authors mined their personal data archives for their printed works, charging their writing with a distinctive aesthetic whose trace is preserved in the process of their works' remediation from digital media to print. Creating their work in the course of this platform-hopping, these writers take a unique poetic measure of our social media landscape. A social media poetics has emerged in Alt Lit, found at the intersection of three important aspects of the movement: an examination of its contemporary relevance; an analysis of the lyricization process that takes place when social media posts are remediated for the printed page; and a delineation of Alt Lit's poetic genealogy, which encompasses Charles Olson and the Beats, their relationships with technology, and the formal influence of subsequent developments in the history of communication technologies. Section 1 provides a brief history of Alt Lit's rise and fall, highlighting features of the movement that illustrate its contemporary relevance and recommend it for analysis and critique in the current moment. Two longer sections augment these claims for significance with arguments that situate Alt Lit within the context of past and present poetic theories and practices. Section 2 combines close readings with the framework of lyric reading to reveal shifts that occur when text that originates on social media is reworked for poetry's printed page. During this process, a solitary speaking voice that invites a lyric reading is foregrounded. At the same time, however, the verse line preserves an essential formal relationship with the social media post that is concealed by the logic of lyric reading. Finally, section 3 positions Alt Lit writers as successors to a developing tradition, articulated by Olson and [End Page 598] consolidated by the Beats, which linked the verse line with the poet's breath. Principles similar to those that informed Olson's theory featured prominently in the development of mobile communications technologies so that a distinct line connects these poetic theories and practices, and their engagements with technology, to Alt Lit. Together, these three sections identify and analyze the contemporary and historic underpinnings of the social media poetics that characterize Alt Lit. ALT LIT TODAY During its peak in the 2010s, Alt Lit (sometimes hyphenated) attracted equal measures of acclaim and disdain. While detractors characterized the movement as the work of "boring, infantile narcissists," other critics celebrated its tonal and stylistic emulation of social media by "the first group of young writers grappling with the constant presence of the Internet."3 Although the movement was relatively...

Implementasi Algoritma Rabin Karp Pada Aplikasi Muroja’ah Hafalan Al-Qur’an Menggunakan Google Speech API Berbasis Android

The muroja'ah application in Al-Qur'an memorizing is an android-based application that is used to help memorizers of the Al-Qur’an in doing muroja'ah memorization. The application is built using Speech Recognition in Artificial Intelligence (AI) technology by implementing the Google Speech API and the Rabin Karp Algorithm to convert the user's speech into a string which is then compared with the correct verse string. As for data collection methods, the author uses qualitative research methods, by conducting observations, interviews, and literature research. The application that was built successfully implemented the Google Speech API feature along with the Rabin Karp Algorithm with the output displaying information about the correct status or not along with the percentage accuracy of the similarity between the correct verse data and the voice spoken by the user.

Influence of voice properties on vowel perception depends on speaker context.

Different speakers produce the same intended vowel with very different physical properties. Fundamental frequency (F0) and formant frequencies (FF), the two main parameters that discriminate between voices, also influence vowel perception. While it has been shown that listeners comprehend speech more accurately if they are familiar with a talker's voice, it is still unclear how such prior information is used when decoding the speech stream. In three online experiments, we examined the influence of speaker context via F0 and FF shifts on the perception of /o/-/u/ vowel contrasts. Participants perceived vowels from an /o/-/u/ continuum shifted toward /u/ when F0 was lowered or FF increased relative to the original speaker's voice and vice versa. This shift was reduced when the speakers were presented in a block-wise context compared to random order. Conversely, the original base voice was perceived to be shifted toward /u/ when presented in the context of a low F0 or high FF speaker, compared to a shift toward /o/ with high F0 or low FF speaker context. These findings demonstrate that that F0 and FF jointly influence vowel perception in speaker context.

An Operating Room, Transformed.

An Operating Room, Transformed.

Extending Radio Broadcasting Semantics through Adaptive Audio Segmentation Automations

The present paper focuses on adaptive audio detection, segmentation and classification techniques in audio broadcasting content, dedicated mainly to voice data. The suggested framework addresses a real case scenario encountered in media services and especially radio streams, aiming to fulfill diverse (semi-) automated indexing/annotation and management necessities. In this context, aggregated radio content is collected, featuring small input datasets, which are utilized for adaptive classification experiments, without searching, at this point, for a generic pattern recognition solution. Hierarchical and hybrid taxonomies are proposed, firstly to discriminate voice data in radio streams and thereafter to detect single speaker voices, and when this is the case, the experiments proceed into a final layer of gender classification. It is worth mentioning that stand-alone and combined supervised and clustering techniques are tested along with multivariate window tuning, towards the extraction of meaningful results based on overall and partial performance rates. Furthermore, the current work via data augmentation mechanisms contributes to the formulation of a dynamic Generic Audio Classification Repository to be subjected, in the future, to adaptive multilabel experimentation with more sophisticated techniques, such as deep architectures.

Domesticating: A Meditation on Self-Reliance

Domesticating: A Meditation on Self-Reliance

Do the Nonlinear Dynamic Acoustic Measurements, Nonlinear Energy Difference Ratio and Spectrum Convergence Ratio, Correlate with Perceptual Evaluation of Esophageal Voice Speakers?

The acoustic assessment of phonation after total laryngectomy is challenged by signal aperiodicity which makes frequency-based acoustic measures less reliable. This is important for patients who use esophageal voice since voice samples mostly include type III (highly aperiodic) and 4 (chaotic) signals. As such, using non-linear measures, which are better suited for aperiodic phonation, may be useful to investigate the relationship between acoustic signal characteristics and perception of esophageal voice quality. This study aimed to investigate whether nonlinear dynamic acoustic methods, nonlinear energy difference Ratio (NEDR) and spectrum convergence ratio (SCR), were correlated with perceptual measures in subjects who used esophageal phonation. Thirty-one subjects who had undergone total laryngectomy and use esophageal voice as a rehabilitation method were included in this study. Expert and non-expert raters listened to the esophageal voice samples from the subjects and rated vowels and connected speech samples on a scale from 1 to 7 on dysphonia severity and intelligibility. In addition, non-linear acoustic analysis was performed to calculate NEDR and SCR. Analysis from the raters was compared to the non-linear acoustic analysis to find the correlation between the variables. There were no significant correlations between any of the non-linear acoustic measures NEDR and SCR and the perceptual ratings at the significance level of 0.05. Correlations were calculated for each acoustic measure among the expert raters and among the non-expert raters in both connected speech samples and sustained vowel fragments. In conclusion, the nonlinear dynamic acoustic analyses of spectrum convergence ratio and nonlinear energy difference ratio do not have a significant correlation with perceptual measures of esophageal voice.

The effect of auditory stimulation on pet dogs’ reactions to owner separation

The domestic dog has attracted notable attention in relation to the welfare benefits of auditory stimulation. Studies carried out in rescue kennels, an environment in which dogs are prone to chronic stress, have pointed to a calming influence of both classical music and audiobooks. The benefits of auditory stimulation for dogs experiencing more immediate types of stress, however, are still unknown. This investigation thus examined the effect of classical music and the spoken voice in the form of an audiobook on the behaviour of pet dogs in response to separation from their owners, a known short-term stressor. Three conditions of auditory stimulation were employed: (1) a control (the normal environment of the university research room), (2) classical music (Mozart’s Sonata K.448) and (3) an audiobook (Harry Potter and the Philosopher’s Stone). The effect of these conditions was explored using two approaches. Study 1 explored the effects of auditory stimulation using a between-subjects design. Sixty dogs were assigned to one of the 3 conditions and exposed to the relevant auditory stimulus for 1-hour. Each dog’s behaviour was recorded every 10 s using a purpose-designed ethogram. Latency data were recorded by video. Results revealed a significant effect of auditory condition on latency to lie down, latency to settle (i.e., lie down for >30 s) and speaker-directed gaze. Dogs exposed to classical music were significantly faster to lie down than animals in the audiobook condition and quicker to settle than animals in the audiobook and control conditions. Subjects in the audiobook condition spent significantly more time gazing at the speaker than animals in the classical music and control conditions. Dogs in the classical music condition also spent significantly more time looking towards the speaker than control animals. Study 2 examined the effects of auditory stimulation using a repeated measures design. Twenty-two dogs were exposed to each condition of auditory stimulation for 30 min, with a period of 10 min between conditions. Each animal’s behaviour was recorded as per Study 1. Only speaker-directed gaze differed significantly between conditions, with animals spending more time looking at the speaker in the audiobook and classical music conditions than the control. Overall, findings point to only a moderately calming effect of classical music, and no apparent welfare benefits of an audiobook, on dogs separated from their owners. The research points to auditory stimulation having little value to dogs in situations of short-term acute stress. Further research is recommended in this field, ideally in a wider variety of contexts than studied thus far.

Gender Voice Recognition Using Machine Learning Algorithms

Abstract: Gender identification is one of the major problems in the area of signal processing. The system deals with finding the gender of a person using oral features. One of the most persnickety problems faced is feature selection from wide range of features, which is distinguishing factor in classifying the gender of aperson. The ideal of this design is to design a system that determines the speaker gender using the pitch of the speaker's voice. relating the gender from the plots of voice data set i.e., pitch, median, frequency etc. can be possible by using machine learning. In this design, we're trying to classify gender into male or female based on the data set containing varied attributes related to voice like pitch, frequency etc. The data set have features with explanation data points recorded samples of male and female voices. The data set can be trained with different machine learning algorithms. The proposed system can determine the gender of the speaker with real time test data a new result to discover the gender of the speaker using Fast Fourier Transform with Logistic Regression

Intelligibility and Recognition of Announcer's Speech during Electric Acoustic Conversions in a Transformer

The purpose of the article is to outline the procedure and the results of the study of the influence of the distance from the sound source to the transformer on speech intelligibility and speaker recognition by voice during electro-acoustic conversion in a transformer. Of all the existing methods for measuring speech intelligibility and voice recognition, the objectified method of articulatory syllabary tables was used. The choice of the method is due to the fact that with a large number of dictated and, accordingly, adopted syllables, the influence of various factors is averaged out. Averaging also occurs if different groups of speakers and auditors take part in the tests. This is the objectivity of the articulatory method. Objective results can also be obtained by using speech to precisely reproduce sound combinations that do not have a semantic load, since when receiving words or phrases, it is possible to think out and restore the elements of the speech distorted by the communication path. The experimental procedure was determined. For the study, a transformer was used as an electroacoustic transducer, and a multifunctional search device ST031M “Piranha” was used as a control and measuring equipment. The selection of speakers and auditors was carried out for the research team. The selection was carried out among men and women between the ages of 18 and 30 who had no obvious speech and hearing impairments and were native speakers of the Russian language. The dependences of the values of the level of speech intelligibility and recognition of the speaker's voice on the distance between the sound source and the transformer are derived. The distances from the sound source to the transformer are determined, at which speech intelligibility corresponds to different quality classes according to GOST 16600-72.

Voice Cloning Applied to Voice Disorders: a Study of Extreme Phonetic Content in Speaker Embeddings

Organic dysphonia can lead to vocal impairments. Recording patients' impaired voice could allow them to use voice cloning systems. In the domain of speech synthesis, voice cloning is the process of producing speech matching a target speaker voice, given textual input and an audio sample from the speaker. It can achieve high-quality speech with only few data from the target speaker. However, dysphonic patients may only produce speech with specific or limited phonetic content. To our knowledge, the impact of such constraints on a voice cloning system remains to be studied. This article presents the results of preliminary experiments on the matter, along with specifications about the models and datasets used.

Disclosing Critical Voice Features for Discriminating between Depression and Insomnia-A Preliminary Study for Developing a Quantitative Method.

Background: Depression and insomnia are highly related—insomnia is a common symptom among depression patients, and insomnia can result in depression. Although depression patients and insomnia patients should be treated with different approaches, the lack of practical biological markers makes it difficult to discriminate between depression and insomnia effectively. Purpose: This study aimed to disclose critical vocal features for discriminating between depression and insomnia. Methods: Four groups of patients, comprising six severe-depression patients, four moderate-depression patients, ten insomnia patients, and four patients with chronic pain disorder (CPD) participated in this preliminary study, which aimed to record their speaking voices. An open-source software, openSMILE, was applied to extract 384 voice features. Analysis of variance was used to analyze the effects of the four patient statuses on these voice features. Results: statistical analyses showed significant relationships between patient status and voice features. Patients with severe depression, moderate depression, insomnia, and CPD reacted differently to certain voice features. Critical voice features were reported based on these statistical relationships. Conclusions: This preliminary study shows the potential in developing discriminating models of depression and insomnia using voice features. Future studies should recruit an adequate number of patients to confirm these voice features and increase the number of data for developing a quantitative method.

The Body and Figurative Language in Ben Jonson's Epigram CXXV, “To Sir William Uvedale”

This essay argues that the relationship between the body and figurative language is central to Ben Jonson's epideictic poetry. In his poetry of praise, Jonson attempts to anchor a disembodied speaking voice in the bodies of those to whom his poetry is addressed. Generated by the bodies of others, Jonson's figurative language asserts and even depends for its success upon the speaker's incorporeality. Yet, I will argue, in Jonson's poetry in general and his epideictic poetry in particular, the body is not just the object of discourse but also the subject of discourse; the interplay between the two shapes Jonson's figurative language even in the case of a poem, such as epigram CXXV, “To Sir William Uvedale,” that seems to have very little to do with the body. The epigram is neither Petrarchan love poem, satire, nor an indulgence in the grotesque. Nonetheless, it is structured by Jonson's attempt to deny the male body as the ground of its figurative language, a denial that is itself rooted in bodily metaphors. The failure of the attempted denial reveals at once the figurative, back-constructed nature of the ostensibly literal object of the poem, Uvedale's body, and the very embodied nature of the supposedly disembodied, transcendental speaker.

‘This app can help you change your voice’: Authenticity and authority in mobile applications for transgender voice training

Mobile applications for transgender voice training seek to help trans people alter their speaking voices, often with the goal of alignment with one or another pole of binary gender expression (i.e., voice ‘feminization’ or ‘masculinization’). These apps offer instruction, audio tools and feedback mechanisms that allow users to record, evaluate and track their progress relative to a desired – and gendered – goal. As with digital technologies generally, however, these apps draw on and reproduce particular ideas of both the needs and capacities of imagined users and broader social and political phenomena – in this case, voice, gender expression and gender transition. In the following paper, we undertake a critical discourse analysis of five mobile voice training apps for transgender people. We find that rather than offering expansive or open-ended conceptions of gender, these apps reproduce ideals of gender as not only binary but also white, affluent and able-bodied. We also offer a critique of the apps’ characterization of transition as reifying the normative authority of clinical and technoscientific knowledge and conditioning ‘authenticity’ on an ability to conform to (racialized, classed and ableist) binary gender norms.

Contributions of Forward-Focused Voice to Audio-Vocal Feedback Measured Using Nasal Accelerometry and Power Spectral Analysis of Vocal Fundamental Frequency.

The spectral powers of the modulations of vocal fundamental frequency (f o) less than 3 Hz (low-frequency power, LFP) and between 3 and 8 Hz (middle-frequency power, MFP) had been established to indicate the audio-vocal feedback status and vocal efficiency of a speaker, and a resonant voice may enhance the auditory-vocal feedback. This study aims to determine whether the auditory feedback can be augmented by a forward and resonant voice and therefore contribute to the modulations of f o variability. Vocal signals and accelerometric signals of lateral nasal cartilage were obtained from 27 healthy adults who, respectively, sustained vowels /a/ and /i/ with their habitual speaking voice and with a forward-focused voice under three auditory conditions: natural hearing (N0), high-level noise exposure (N90), and low-level noise exposure (N60). Nasal skin vibrations were measured using a nasal accelerometry to reflect voice resonance status. Vocal intensity and f o variability were also analyzed to show the auditory-vocal interactions under varied conditions of auditory feedback and voice resonance. In both N0 and N90 conditions, forward-focused voice showed a significantly lower LFP than the speakers' habitual voice. In addition, LFP of f o would significantly increase during natural voice production as the voice feedback was greatly masked by high-intensity noise; however, with a forward-focused voice, the noise-induced variation in LFP was significantly decreased. Under N90, MFP significantly decreased during forward-focused voice production compared with that measured during natural voice production. The stability of f o modulations was not adversely affected by N60. The results support the idea that vocalizing with a forward-focused voice enhance the auditory feedback of the speaker's own voice and, thus, reduce the variability of f o during sustained phonation, especially when vocalizing in the high noise condition.

Difficulties Experienced by Older Listeners in Utilizing Voice Cues for Speaker Discrimination.

Human listeners are assumed to apply different strategies to improve speech recognition in background noise. Young listeners with normal hearing (NH), e.g., have been shown to follow the voice of a particular speaker based on the fundamental (F0) and formant frequencies, which are both influenced by the gender, age, and size of the speaker. However, the auditory and cognitive processes that underlie the extraction and discrimination of these voice cues across speakers may be subject to age-related decline. The present study aimed to examine the utilization of F0 and formant cues for voice discrimination (VD) in older adults with hearing expected for their age. Difference limens (DLs) for VD were estimated in 15 healthy older adults (65–78 years old) and 35 young adults (18–35 years old) using only F0 cues, only formant frequency cues, and a combination of F0 + formant frequencies. A three-alternative forced-choice paradigm with an adaptive-tracking threshold-seeking procedure was used. Wechsler backward digit span test was used as a measure of auditory working memory. Trail Making Test (TMT) was used to provide cognitive information reflecting a combined effect of processing speed, mental flexibility, and executive control abilities. The results showed that (a) the mean VD thresholds of the older adults were poorer than those of the young adults for all voice cues, although larger variability was observed among the older listeners; (b) both age groups found the formant cues more beneficial for VD, compared to the F0 cues, and the combined (F0 + formant) cues resulted in better thresholds, compared to each cue separately; (c) significant associations were found for the older adults in the combined F0 + formant condition between VD and TMT scores, and between VD and hearing sensitivity, supporting the notion that a decline with age in both top-down and bottom-up mechanisms may hamper the ability of older adults to discriminate between voices. The present findings suggest that older listeners may have difficulty following the voice of a specific speaker and thus implementing doing so as a strategy for listening amid noise. This may contribute to understanding their reported difficulty listening in adverse conditions.

E-Diwan App: The 21st Century Solution for Teaching and Learning Arabic Poetry

Arabic language is a global language and has become one of the most important languages for all language learners around the world. A fundamental component of sound Arabic language acquisition is Arabic poetry which is innately intricate. Hence, deficiency in interactive computer programs specially designed for learning Arabic poetry, has generated apathy that Arabic poetry is superfluous, consequently ensuing impotence to the graduates of Arabic Language and Literature Studies. The existing scenario illustrates the preference and reliance on interactive programs and gadgets among the educators and students. E-Diwan enables the accessibility of teaching and learning Arabic poetry through a mobile device and a mobile interface (Android, iPhone, Windows Mobile) with a designated Arabic poetry electronic portfolio website. E-Diwan keeps the students glued to the screen and are dazzled by the atheistic beauty of Arabic poetry subsequently augmenting them with a corpus of Arabic literary lexis. By a click of a button, the app displays a spectrum analysis of the poems; definition, grammatical and rhetorical properties, a brief biography of the poet, and translation of the poems in English and Malay. It is also equipped with the ability to audio present the above information using a recorded voice of an Arabic native speaker. Built-in are videos designed to simultaneously improve the information outcome and performance skills of the user. E-Diwan’s comprehensive nature facilitates individual learning, which cultivates Life Long Learning. E-Diwan fits as a lecture companion tool for all educators teaching Arabic poetry and Arabic language learners.