758 research outputs found

    Challenges with the kinematic analysis of neurotypical and impaired speech : measures and models

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    A common goal of kinematic studies on disordered speech is the identification of speech motor impairments that negatively impact speech function. Although it is well-known that the kinematic contours of speakers with speech disorders often deviate considerably from those of neurotypical speakers, systematic quantitative assessments of these impairment-related movement disturbances remain challenging. Kinematic measurement approaches are commonly grounded in models and theories that have emerged exclusively from observations of healthy speakers. However, often these models cannot accommodate the deviant articulatory behaviors of speakers with speech motor impairment. In the present paper, we address this problem. By considering noise as a factor in Articulatory Phonology/Task Dynamics (AP/TD), we can account for articulatory behaviors that are known to occur in healthy speakers (e.g., during slow speech) as well as in speakers with motor speech impairments. In a proof of concept, we descriptively compare modeled articulatory behaviors that include noise at various levels with empirical data. We view such an extension of the AP/TD as a first step towards a more comprehensive speech production model that can serve as a theoretical framework to study the speech production mechanism in healthy speakers and speakers with motor speech impairments

    Elements, Government, and Licensing: Developments in phonology

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    Elements, Government, and Licensing brings together new theoretical and empirical developments in phonology. It covers three principal domains of phonological representation: melody and segmental structure; tone, prosody and prosodic structure; and phonological relations, empty categories, and vowel-zero alternations. Theoretical topics covered include the formalisation of Element Theory, the hotly debated topic of structural recursion in phonology, and the empirical status of government. In addition, a wealth of new analyses and empirical evidence sheds new light on empty categories in phonology, the analysis of certain consonantal sequences, phonological and non-phonological alternation, the elemental composition of segments, and many more. Taking up long-standing empirical and theoretical issues informed by the Government Phonology and Element Theory, this book provides theoretical advances while also bringing to light new empirical evidence and analysis challenging previous generalisations. The insights offered here will be equally exciting for phonologists working on related issues inside and outside the Principles & Parameters programme, such as researchers working in Optimality Theory or classical rule-based phonology

    Acquiring a second language during childhood: a case study of the acquisition of English by a child Kazakh speaker

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    In this dissertation, we document a child Kazakh speaker’s acquisition of English as her second language. In particular, we focus on this child’s development of the English segments |f, v, θ, ð, ɹ, ʃ, ʧ|, and her acquisition of the English copula be, third person singular -s, and past tense -ed. We begin with detailed, longitudinal description of the developmental patterns that the child displayed through her acquisition of each of these segments and morphemes over an approximately two-year period. Building on our data descriptions, we entertain a feature-based approach to analyze the patterns observed. We analyze the child’s acquisition of English consonants by following the Phonological Interference Hypothesis by Brown (1998), as well as the feature redistribution and recombination theory by Martinez, Goad & Dow (2021).These models highlight the possibilities of maximal transfer of the L1 features, and the possibilities of feature recombination in the course of L2 acquisition. Similarly, we analyze the child’s acquisition of inflectional morphology through the Missing Surface Inflection Hypothesis (MSIH) by Prévost & White (2000), which highlights both the presence of syntactic features in the child’s interlanguage grammar and the difficulties inherent to the morphological expression of these features in speech. As we will see, however, feature-based analyses do not enable an account for all of the facts. The data highlights the need to consider other factors, including language-specific ‘surface’ knowledge. Concerning segmental development, we show the need to consider phonetic features, which define the precise motor articulations required in the production of speech sounds. Likewise, concerning morphological development, we show the need to consider of language-specific aspects of morphological expressions in spoken forms, in relation to the underlying syntactic knowledge

    Music and musicality in brain surgery:The effect on delirium and language

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    Delirium is a neuropsychiatric clinical syndrome with overlapping symptoms withthe neurologic primary disease. This is why delirium is such a difficult and underexposedtopic in neurosurgical literature. Delirium is a complication which mightaffect recovery after brain surgery, hence we describe in Chapter 2 a systematicreview which focuses on how delirium is defined in the neurosurgical literature.We included twenty-four studies (5589 patients) and found no validation studiesof screening instruments in neurosurgical papers. Delirium screening instruments,validated in other cohorts, were used in 70% of the studies, consisting of theConfusion Assessment Method (- Intensive Care Unit) (45%), Delirium ObservationScreening Scale (5%), Intensive Care Delirium Screening Checklist (10%), Neelonand Champagne Confusion Scale (5%), and Nursing Delirium Screening Scale (5%).Incidence of post-operative delirium after intracranial surgery was 19%, ranging from12 – 26% caused by variation in clinical features and delirium assessment methods.Our review highlighted the need of future research on delirium in neurosurgery,which should focus on optimizing diagnosis, and assessing prognostic significanceand management.It is unclear what the impact of delirium is on the recovery after brain surgery,as delirium is often a self-limiting and temporary complication. In Chapter 3 wetherefore investigated the impact of delirium, by means of incidence and healthoutcomes, and identified independent risk factors by including 2901 intracranialsurgical procedures. We found that delirium was present in 19.4% with an averageonset (mean/SD) within 2.62/1.22 days and associated with more Intensive CareUnit (ICU) admissions and more discharge towards residential care. These numbersconfirm the impact of delirium with its incidence rates, which were in line with ourprevious systematic review, and significant health-related outcomes. We identifiedseveral independent non-modifiable risk factors such as age, pre-existing memoryproblems, emergency operations, and modifiable risk factors such as low preoperativepotassium and opioid and dexamethasone administration, which shed lighton the pathophysiologic mechanisms of POD in this cohort and could be targetedfor future intervention studies.10As listening to recorded music has been proven to lower delirium-eliciting factors inthe surgical population, such as pain, we were interested in the size of analgesic effectand its underlying mechanism before applying this into our clinical setting. In Chapter4 we describe the results of a two-armed experimental randomized controlled trial inwhich 70 participants received increasing electric stimuli through their non-dominantindex finger. This study was conducted within a unique pain model as participantswere blinded for the outcome. Participants in the music group received a 20-minutemusic intervention and participants in the control group a 20-minute resting period.Although the effect of the music intervention on pain endurance was not statisticallysignificant in our intention-to-treat analysis (p = 0.482, CI -0.85; 1.79), the subgroupanalyses revealed an increase in pain endurance in the music group after correcting fortechnical uncertainties (p = 0.013, CI 0.35; 2.85). This effect on pain endurance couldbe attributed to increased parasympathetic activation, as an increased Heart RateVariability (HRV) was observed in the music vs. the control group (p=0.008;0.032).As our prior chapters increased our knowledge on the significance of delirium on thepost-operative recovery after brain surgery and the possible beneficial effects of music,we decided to design a randomized controlled trial. In Chapter 5 we describe theprotocol and in Chapter 6 we describe the results of this single-centered randomizedcontrolled trial. In this trial we included 189 patients undergoing craniotomy andcompared the effects of music administered before, during and after craniotomy withstandard of clinical care. The primary endpoint delirium was assessed by the deliriumobservation screening scale (DOSS) and confirmed by a psychiatrist accordingto DSM-5 criteria. A variety of secondary outcomes were assessed to substantiatethe effects of music on delirium and its clinical implications. Our results supportthe efficacy of music in preventing delirium after craniotomy, as found with DOSS(OR:0.49, p=0.048) but not after DSM-5 confirmation (OR:0.47, p=0.342). Thispossible beneficial effect is substantiated by the effect of music on pre-operativeautonomic tone, measured with HRV (p=0.021;0.025), and depth of anesthesia(p=&lt;0.001;0.022). Our results fit well within the current literature and support theimplementation of music for the prevention of delirium within the neurosurgicalpopulation. However, delirium screening tools should be validated and the long-termimplications should be evaluated after craniotomy to assess the true impact of musicafter brain surgery.Musicality and language in awake brain surgeryIn the second part of this thesis, the focus swifts towards maintaining musicality andlanguage functions around awake craniotomy. Intra-operative mapping of languagedoes not ensure complete maintenance which mostly deteriorates after tumor resection.Most patients recover to their baseline whereas other remain to suffer from aphasiaaffecting their quality of life. The level of musical training might affect the speed andextend of postoperative language recovery, as increased white matter connectivity inthe corpus callosum is described in musicians compared to non-musicians. Hence,in Chapter 7 we evaluate the effect of musicality on language recovery after awakeglioma surgery in a cohort study of forty-six patients. We divided the patients intothree groups based on the musicality and compared the language scores between thesegroups. With the first study on this topic, we support that musicality protects againstlanguage decline after awake glioma surgery, as a trend towards less deterioration oflanguage was observed within the first three months on the phonological domain (p= 0.04). This seemed plausible as phonology shares a common hierarchical structurebetween language and singing. Moreover, our results support the hypothesis ofmusicality induced contralateral compensation in the (sub-) acute phase through thecorpus callosum as the largest difference of size was found in the anterior corpuscallosum in non- musicians compared to trained musicians (p = 0.02).In Chapter 8 we addressed musicality as a sole brain function and whether it canbe protected during awake craniotomy in a systematic review consisting of tenstudies and fourteen patients. Isolated music disruption, defined as disruption duringmusic tasks with intact language/speech and/or motor functions, was identified intwo patients in the right superior temporal gyrus, one patient in the right and onepatient in the left middle frontal gyrus and one patient in the left medial temporalgyrus. Pre-operative functional MRI confirmed these localizations in three patients.Assessment of post-operative musical function, only conducted in seven patients bymeans of standardized (57%) and non-standardized (43%) tools, report no loss ofmusical function. With these results we concluded that mapping music is feasibleduring awake craniotomy. Moreover, we identified certain brain regions relevant formusic production and detected no decline during follow-up, suggesting an addedvalue of mapping musicality during awake craniotomy. A systematic approach to mapmusicality should be implemented, to improve current knowledge on the added valueof mapping musicality during awake craniotomy.<br/

    Northeastern Illinois University, Academic Catalog 2023-2024

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    https://neiudc.neiu.edu/catalogs/1064/thumbnail.jp

    Imagining & Sensing: Understanding and Extending the Vocalist-Voice Relationship Through Biosignal Feedback

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    The voice is body and instrument. Third-person interpretation of the voice by listeners, vocal teachers, and digital agents is centred largely around audio feedback. For a vocalist, physical feedback from within the body provides an additional interaction. The vocalist’s understanding of their multi-sensory experiences is through tacit knowledge of the body. This knowledge is difficult to articulate, yet awareness and control of the body are innate. In the ever-increasing emergence of technology which quantifies or interprets physiological processes, we must remain conscious also of embodiment and human perception of these processes. Focusing on the vocalist-voice relationship, this thesis expands knowledge of human interaction and how technology influences our perception of our bodies. To unite these different perspectives in the vocal context, I draw on mixed methods from cog- nitive science, psychology, music information retrieval, and interactive system design. Objective methods such as vocal audio analysis provide a third-person observation. Subjective practices such as micro-phenomenology capture the experiential, first-person perspectives of the vocalists them- selves. Quantitative-qualitative blend provides details not only on novel interaction, but also an understanding of how technology influences existing understanding of the body. I worked with vocalists to understand how they use their voice through abstract representations, use mental imagery to adapt to altered auditory feedback, and teach fundamental practice to others. Vocalists use multi-modal imagery, for instance understanding physical sensations through auditory sensations. The understanding of the voice exists in a pre-linguistic representation which draws on embodied knowledge and lived experience from outside contexts. I developed a novel vocal interaction method which uses measurement of laryngeal muscular activations through surface electromyography. Biofeedback was presented to vocalists through soni- fication. Acting as an indicator of vocal activity for both conscious and unconscious gestures, this feedback allowed vocalists to explore their movement through sound. This formed new perceptions but also questioned existing understanding of the body. The thesis also uncovers ways in which vocalists are in control and controlled by, work with and against their bodies, and feel as a single entity at times and totally separate entities at others. I conclude this thesis by demonstrating a nuanced account of human interaction and perception of the body through vocal practice, as an example of how technological intervention enables exploration and influence over embodied understanding. This further highlights the need for understanding of the human experience in embodied interaction, rather than solely on digital interpretation, when introducing technology into these relationships

    Language variation, automatic speech recognition and algorithmic bias

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    In this thesis, I situate the impacts of automatic speech recognition systems in relation to sociolinguistic theory (in particular drawing on concepts of language variation, language ideology and language policy) and contemporary debates in AI ethics (especially regarding algorithmic bias and fairness). In recent years, automatic speech recognition systems, alongside other language technologies, have been adopted by a growing number of users and have been embedded in an increasing number of algorithmic systems. This expansion into new application domains and language varieties can be understood as an expansion into new sociolinguistic contexts. In this thesis, I am interested in how automatic speech recognition tools interact with this sociolinguistic context, and how they affect speakers, speech communities and their language varieties. Focussing on commercial automatic speech recognition systems for British Englishes, I first explore the extent and consequences of performance differences of these systems for different user groups depending on their linguistic background. When situating this predictive bias within the wider sociolinguistic context, it becomes apparent that these systems reproduce and potentially entrench existing linguistic discrimination and could therefore cause direct and indirect harms to already marginalised speaker groups. To understand the benefits and potentials of automatic transcription tools, I highlight two case studies: transcribing sociolinguistic data in English and transcribing personal voice messages in isiXhosa. The central role of the sociolinguistic context in developing these tools is emphasised in this comparison. Design choices, such as the choice of training data, are particularly consequential because they interact with existing processes of language standardisation. To understand the impacts of these choices, and the role of the developers making them better, I draw on theory from language policy research and critical data studies. These conceptual frameworks are intended to help practitioners and researchers in anticipating and mitigating predictive bias and other potential harms of speech technologies. Beyond looking at individual choices, I also investigate the discourses about language variation and linguistic diversity deployed in the context of language technologies. These discourses put forward by researchers, developers and commercial providers not only have a direct effect on the wider sociolinguistic context, but they also highlight how this context (e.g., existing beliefs about language(s)) affects technology development. Finally, I explore ways of building better automatic speech recognition tools, focussing in particular on well-documented, naturalistic and diverse benchmark datasets. However, inclusive datasets are not necessarily a panacea, as they still raise important questions about the nature of linguistic data and language variation (especially in relation to identity), and may not mitigate or prevent all potential harms of automatic speech recognition systems as embedded in larger algorithmic systems and sociolinguistic contexts
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