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Andrew Valenti

Tufts University, Cognitive Science, Graduate Student

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I’ve been fortunate to observe the evolution of the IT industry from providing computers that not much more than calculators and electronic typewriters, to the growth of enterprise-wide processing systems, and to, at present, ubiquitous personal digital assistance. My belief is that the next wave of computing will be not to replace human thinking, but to augment and accelerate human learning. My objective is to take the technology and educator skills I’ve developed over the past 25 years and focus on creating tools to improve teaching, learning, and collaboration across languages and cultures.
Phone: 617.627.3814
Address: Tufts University
169 Holland Street
Suite 317B
Somerville, MA 02144

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Morten H. Christiansen

Cornell University

Vrije Universiteit Brussel

Canadian University of Dubai

George K. # Zarifis

Aristotle University of Thessaloniki

Universidad Nacional de Colombia (National University of Colombia)

University of Delhi

Albert Bastardas-Boada

Universitat de Barcelona

Kwantlen Polytechnic University

The George Washington University

Armando Marques-Guedes

UNL - New University of Lisbon

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Papers by Andrew Valenti

Correspondence between spectral reflectance and features of the built environment for community resilience

Geospatial Informatics XII

An NLP approach to quantify dynamic salience of predefined topics in a text corpus

arXiv (Cornell University), Aug 16, 2021

The proliferation of news media available online simultaneously presents a valuable resource and ... more The proliferation of news media available online simultaneously presents a valuable resource and significant challenge to analysts aiming to profile and understand social and cultural trends in a geographic location of interest. While an abundance of news reports documenting significant events, trends, and responses provides a more democratized picture of the social characteristics of a location, making sense of an entire corpus to extract significant trends is a steep challenge for any one analyst or team. Here, we present an approach using natural language processing techniques that seeks to quantify how a set of predefined topics of interest change over time across a large corpus of text. We found that, given a predefined topic, we can identify and rank sets of terms, or n-grams, that map to those topics and have usage patterns that deviate from a normal baseline. Emergence, disappearance, or significant variations in n-gram usage present a ground-up picture of a topic's dynamic salience within a corpus of interest.

An adaptive learning model for predicting and analyzing student performance on flight training tasks

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI

In Their Own Words: A Companion Robot for Detecting the Emotional State of Persons with Parkinson’s Disease

Social Robotics, 2019

In typical human interactions emotional states are communicated via a variety of modalities such ... more In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations, as in the case of facial masking in Parkinson’s disease (PD). In these cases, we need to focus the communication and detection of emotions on the reliable modalities, by inferring emotions from what is being said, and compensate for the modalities that are problematic, by having another agent (e.g., a robot) provide the missing facial expressions. We describe the initial development stage of a robot companion that can assist the communication and detection of emotions in interactions where some modalities are totally or partially compromised. Such is the case for people living with Parkinson’s disease.

A Neural Field Model of Word Repetition Effects in Early Time-Course ERPs in Spoken Word Perception

Cognitive Science, 2016

Previous attempts at modeling the neuro-cognitive mechanisms underlying word processing have used... more Previous attempts at modeling the neuro-cognitive mechanisms underlying word processing have used connectionist approaches, but none has modeled spoken word architectures as the input is presented in real-time. Hence, such models rely on the ingenuity of the modeler to establish a mapping of realtime stimulus to the model’s input which may not preserve processing that happens during each time step. We present a neural field model which successfully replicates the effect of immediate auditory repetition of monosyllabic words and fits it to a component of a well-studied mechanism for analyzing language processing, the event-related potential (ERP). This represents a new modeling approach to studying the neurocognitive processes, one that is based on the bottom-up interaction of real-time sensory information with higher-level categories of cognitive processing.

A computational model of bilingual inhibitory control in a lexical decision task

Results from empirical studies in bilingual research demonstrate that “code-switching” in bilingu... more Results from empirical studies in bilingual research demonstrate that “code-switching” in bilinguals, i.e., the change from one language to another, comes at a cost. What is still unclear is the exact nature of the cost. In this paper, we develop a connectionist model of Green’s Inhibitory Control (IC) hypothesis for a bilingual lexical decision task (Green, 1998, 74), which hypothesizes that the cost of switching between two languages in this task is due to inhibitory forces among different task schema and word forms. We were able to fit the model to the empirical data from Von Studnitz and Green (1997, Experiment 1), thus providing a proof-of-concept model that the IC hypothesis can account for the observed language switching costs and for the L1 language advantage effect in a lexical decision task. More extensive, systematic explorations of the model and its parameters in related but different tasks are, however, required to determine the extent of the IC applicability. Although ...

A Multi-level Framework for Understanding Spoken Dialogue Using Topic Detection

Spoken Dialogue Systems (SDS) are used to interact with intelligent agents through natural langua... more Spoken Dialogue Systems (SDS) are used to interact with intelligent agents through natural language. Speech processing errors may cause the system to fail to generate an appropriate response. In this paper, we present a novel framework for understanding spoken dialogue in which utterance analysis is escalated through a multi-level system according to the feedback retrieved at the syntactic, semantic, and contextual/topic level. Analysis is applied incrementally at each level as the system attempts to resolve the uncertainty surrounding utterance interpretation. We demonstrate how our multi-level approach can be integrated with other SDS components to improve its ability to recognize spoken task commands. We evaluate this by comparing the interpretation accuracy of utterances from two task domains given as input to an SDS, under two experimental conditions: one with the multi-level framework and one without. Figure 1: Typical spoken dialogue system. At each turn t, input speech is co...

A Neural Field Model of Sequence Perception

We show how temporal and spatial information can be represented as stable patterns in a dynamical... more We show how temporal and spatial information can be represented as stable patterns in a dynamical system. It is hypothesized that human perception and knowledge representation arise from such patterns. We describe how these patterns can be used in a neurologically-inspired model of speech perception, and show how word recognition arises when phonemes and their position in a word are mapped onto activation patterns. These activation patterns are used to identify the set of words whose prefix is the corresponding sequence, consistent with the “cohort”-based model of word recognition.

A Neural Field Model of Word Recognition

We show how temporal and spatial information can be represented as stable patterns in a dynamical... more We show how temporal and spatial information can be represented as stable patterns in a dynamical system. We describe a model in which category perception arises from the incremental recognition of temporal patterns from sequences of inputs and this is accomplished by decoding a pool of recurrently connected artificial neurons which is called a neural field. In an example application, we use these patterns to identify a set of words which share the word onset represented by the input sequence, consistent with the Marslen-Wilson COHORT model of word recognition. Similarly, we evaluate the extent to which information contained in the bottom-up sensory signal can be used to determine word boundaries. We suggest it is plausible that a neural field offers a naturalistic explanation of how perception arises in word processing.

In Their Own Words: A Companion Robot for Detecting the Emotional State of Persons with Parkinson's Disease

In typical human interactions emotional states are communicated via a variety of modalities such ... more In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations, as in the case of facial masking in Parkinson’s disease (PD). In these cases, we need to focus the communication and detection of emotions on the reliable modalities, by inferring emotions from what is being said, and compensate for the modalities that are problematic, by having another agent (e.g., a robot) provide the missing facial expressions. We describe the initial development stage of a robot companion that can assist the communication and detection of emotions in interactions where some modalities are totally or partially compromised. Such is the case for people living with Parkinson’s disease.

Data distribution apparatus and method having a data description including information for specifying a time that a data distribution is to occur

Using topic modeling to infer the emotional state of people living with Parkinson’s disease

Emotion expression in a socially assistive robot for persons with Parkinson's disease

Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Emotions are crucial for human social interactions and thus people communicate emotions through a... more Emotions are crucial for human social interactions and thus people communicate emotions through a variety of modalities: kinesthetic (through facial expressions, body posture and gestures), auditory (the acoustic features of speech) and semantic (the content of what they say). Sometimes however, communication channels for certain modalities can be unavailable (e.g., in the case of texting), and sometimes they can be compromised, due to a disorder such as Parkinson's disease (PD) that may aect facial, gestural and speech expressions of emotions. To address this, we developed a prototype for an emoting robot that can detect emotions in one modality, specically in the content of speech, and then express them in another modality, specically through gestures. The system consists of two components: detection and expression of emotions. In this paper we present the development of the expression component of the emoting system. We focus on its dynamical properties that use a spring model for smooth transitions between emotion expressions over time. This novel method compensates for varying utterance frequency and prediction errors coming from the emotion recognition component. We also describe the input the dynamical expression component receives from the emotion detection component, the development and validation of the output comprising of the gestures instantiated in the robot, and the implementation of the system. We present results from a human validation study that shows people perceive the robot gestures, generated by the system, as expressing the emotions in the speech content. Also, we show that people's perceptions of the accuracy of emotion expression is signicantly higher for a mass-spring dynamical system than a system without a mass-spring when specic detection errors are present. We discuss and suggest future developments of the system and further validation experiments. This paper is part of a larger project to develop a prototype for a socially assistive robot for PD persons. The goal is to present the

A Survey of the Neurological Evidence for Language Selection in Bilingual Speech Production

The "hard problem" in speech production is embodied in the cognitive process which selects the si... more The "hard problem" in speech production is embodied in the cognitive process which selects the single, correct word that the speaker intends to utter from among multiple words activated by their shared semantic concept. Bilingual word selection is even harder because of the generally held assumption that concept selection also activates both of the speaker’s languages to an approximately equal extent.
Several competing hypothesis based on behavioral experiments attempt to explain the hard problem were reviewed by Finkbeiner, M., Gollan, T., & Caramazza, A. (2006). The authors suggest none to be entirely correct and that a simpler cognitive mechanism, selection-by-threshold, best explains many of the observed facilitatory and inhibitory cross-language effects. Subsequent research by Kroll et al. (2008) and Golan & Ferreira (2007) suggests that behavioral studies, specifically those that examine asymmetrical language switching costs in and of itself may not reveal the means of lexical selection.
Rather than relying on behavioral studies, more recent research has examined the evidence on the neural basis of language selection which suggests that inhibitory control is required to enable the bilinguals to speak one language alone. This paper seeks to review the research and identify the consensus, if one exists, on the neurological structures that serve as the locus of language selection and control.

A computational model of bilingual inhibitory control in a lexical decision task

Results from empirical studies in bilingual research demonstrate that “code-switching” in biling... more Results from empirical studies in bilingual research demonstrate
that “code-switching” in bilinguals, i.e., the change from
one language to another, comes at a cost. What is still unclear
is the exact nature of the cost. In this paper, we develop
a connectionist model for Green’s Inhibitory Control (IC) hypothesis
for a bilingual lexical decision task (Green, 1998, 74),
which hypothesizes that the cost of switching between two languages
in this task is due to inhibitory forces among different
task schema and word forms. We were able to fit the model to
the empirical data from Von Studnitz and Green (1997, Experiment
1), thus providing a proof-of-concept model that the IC
hypothesis can account for the observed language switching
costs. More extensive, systematic explorations of the model
and its parameters in related but different tasks are, however,
required to determine the extent of the IC applicability.

Additional Information Websites: Company Website RSS feed Interests: Sailing, Singing, Guitar, Cooking, Music, Theatre

Research proposal: Does Visual speech prime recognition of interlingual homophones in Dutch-English bilinguals?

This is a proposal to investigate whether lexical input received by a shared auditory and visual ... more This is a proposal to investigate whether lexical input received by a shared auditory and visual speech process can create a priming effect by making contact with the shared bilingual lexicon and activating overlapping phonological representations, consistent with a non-selective control model such as BIA+ (Dijkstra & van Heuven, 2002). This extends past research which has examined cross-language effects but has not provided lexical input through visual speech. It also extends research which has examined visual speech priming but in a monolingual context. In Experiment 1, response times are measured when bilingual Dutch-English participants are presented with a video recording of a bilingual Dutch-English speaker providing a visual speech (i.e., visual + auditory modes) prime of interlingual homophones. Participants are asked whether a target word is English or a non-word. Interlingual homophones are words that have identical phonology across languages but different meanings. An example is /lief/ which means “sweet” in Dutch and pronounced as /leaf/ in English.

Proposal for: An investigation of balanced bilinguals’ use of code switching in inner speech

Speakers of more than one language, (i.e. bilinguals) may intentionally mix their languages durin... more Speakers of more than one language, (i.e. bilinguals) may intentionally mix their languages during conversation in a phenomenon known as “code switching”. As a line of scholarly inquiry, code switching is generally limited to the context of bilingual conversation. I propose to extend the investigation to include inner speech, which is the voice that is often heard inside one’s head while thinking. One view of inner speech is that it is produced using processes similar to that we use to speak except that no utterances are produced. In another view, Vygotsky (1986) posits that inner speech is a child’s ego-centric speech turned inward in a more compact way. For this project, an inner speech discourse is stimulated within proficient Korean-English and Spanish-English bilingual participant s in an experiment by providing one of Kohlberg’s moral dilemmas accompanied by a series of questions probing their responses. Code switching is primed by providing instructions in their native language (L1); the dilemma and probe questions are provided in English. At several points during each session, the participants will be asked to reflect on which language they use for inner speech and the role the language is playing in answering the probes. From this study, I seek an understanding of whether code switching is a mechanism that bilinguals engage in during inner speech activities, how they use it, and what role it plays. Code switching is an area of active research which could become a lens to examine and understand bilinguals’ non-verbal reasoning processes and inform the methods used to present and teach abstract concepts to bilinguals.

UDL in Higher Education

Universal Design for Learning (UDL) is derived from universal design, a name coined by the archit... more Universal Design for Learning (UDL) is derived from universal design, a name coined by the architect Ronald L. Mace for the concept of designing accessibility into buildings, structures, and places from the onset. However, it was the work of Selwyn Goldsmith (1997) originally published in 1963 that put it into practice, the most significant example being the introduction of the cut curb. UDL was developed at the Center for Applied Special Technologies (CAST) in the 1990s and described in the book by David Rose and Ann Myers (2002). As with universal design, UDL’s objective is to increase access to those who have historically been marginalized, and this includes learners who might be considered to have learning disabilities such as dyslexia, but also includes students who are non-native language speakers, who have cultural differences that conflict with the prevailing culture in the learning environment, or those students whose learning style is not coincident with the prevailing learning processes used in the classroom.

Correspondence between spectral reflectance and features of the built environment for community resilience

Geospatial Informatics XII

An NLP approach to quantify dynamic salience of predefined topics in a text corpus

arXiv (Cornell University), Aug 16, 2021

The proliferation of news media available online simultaneously presents a valuable resource and ... more The proliferation of news media available online simultaneously presents a valuable resource and significant challenge to analysts aiming to profile and understand social and cultural trends in a geographic location of interest. While an abundance of news reports documenting significant events, trends, and responses provides a more democratized picture of the social characteristics of a location, making sense of an entire corpus to extract significant trends is a steep challenge for any one analyst or team. Here, we present an approach using natural language processing techniques that seeks to quantify how a set of predefined topics of interest change over time across a large corpus of text. We found that, given a predefined topic, we can identify and rank sets of terms, or n-grams, that map to those topics and have usage patterns that deviate from a normal baseline. Emergence, disappearance, or significant variations in n-gram usage present a ground-up picture of a topic's dynamic salience within a corpus of interest.

An adaptive learning model for predicting and analyzing student performance on flight training tasks

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI

In Their Own Words: A Companion Robot for Detecting the Emotional State of Persons with Parkinson’s Disease

Social Robotics, 2019

In typical human interactions emotional states are communicated via a variety of modalities such ... more In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations, as in the case of facial masking in Parkinson’s disease (PD). In these cases, we need to focus the communication and detection of emotions on the reliable modalities, by inferring emotions from what is being said, and compensate for the modalities that are problematic, by having another agent (e.g., a robot) provide the missing facial expressions. We describe the initial development stage of a robot companion that can assist the communication and detection of emotions in interactions where some modalities are totally or partially compromised. Such is the case for people living with Parkinson’s disease.

A Neural Field Model of Word Repetition Effects in Early Time-Course ERPs in Spoken Word Perception

Cognitive Science, 2016

Previous attempts at modeling the neuro-cognitive mechanisms underlying word processing have used... more Previous attempts at modeling the neuro-cognitive mechanisms underlying word processing have used connectionist approaches, but none has modeled spoken word architectures as the input is presented in real-time. Hence, such models rely on the ingenuity of the modeler to establish a mapping of realtime stimulus to the model’s input which may not preserve processing that happens during each time step. We present a neural field model which successfully replicates the effect of immediate auditory repetition of monosyllabic words and fits it to a component of a well-studied mechanism for analyzing language processing, the event-related potential (ERP). This represents a new modeling approach to studying the neurocognitive processes, one that is based on the bottom-up interaction of real-time sensory information with higher-level categories of cognitive processing.

A computational model of bilingual inhibitory control in a lexical decision task

Results from empirical studies in bilingual research demonstrate that “code-switching” in bilingu... more Results from empirical studies in bilingual research demonstrate that “code-switching” in bilinguals, i.e., the change from one language to another, comes at a cost. What is still unclear is the exact nature of the cost. In this paper, we develop a connectionist model of Green’s Inhibitory Control (IC) hypothesis for a bilingual lexical decision task (Green, 1998, 74), which hypothesizes that the cost of switching between two languages in this task is due to inhibitory forces among different task schema and word forms. We were able to fit the model to the empirical data from Von Studnitz and Green (1997, Experiment 1), thus providing a proof-of-concept model that the IC hypothesis can account for the observed language switching costs and for the L1 language advantage effect in a lexical decision task. More extensive, systematic explorations of the model and its parameters in related but different tasks are, however, required to determine the extent of the IC applicability. Although ...

A Multi-level Framework for Understanding Spoken Dialogue Using Topic Detection

Spoken Dialogue Systems (SDS) are used to interact with intelligent agents through natural langua... more Spoken Dialogue Systems (SDS) are used to interact with intelligent agents through natural language. Speech processing errors may cause the system to fail to generate an appropriate response. In this paper, we present a novel framework for understanding spoken dialogue in which utterance analysis is escalated through a multi-level system according to the feedback retrieved at the syntactic, semantic, and contextual/topic level. Analysis is applied incrementally at each level as the system attempts to resolve the uncertainty surrounding utterance interpretation. We demonstrate how our multi-level approach can be integrated with other SDS components to improve its ability to recognize spoken task commands. We evaluate this by comparing the interpretation accuracy of utterances from two task domains given as input to an SDS, under two experimental conditions: one with the multi-level framework and one without. Figure 1: Typical spoken dialogue system. At each turn t, input speech is co...

A Neural Field Model of Sequence Perception

We show how temporal and spatial information can be represented as stable patterns in a dynamical... more We show how temporal and spatial information can be represented as stable patterns in a dynamical system. It is hypothesized that human perception and knowledge representation arise from such patterns. We describe how these patterns can be used in a neurologically-inspired model of speech perception, and show how word recognition arises when phonemes and their position in a word are mapped onto activation patterns. These activation patterns are used to identify the set of words whose prefix is the corresponding sequence, consistent with the “cohort”-based model of word recognition.

A Neural Field Model of Word Recognition

We show how temporal and spatial information can be represented as stable patterns in a dynamical... more We show how temporal and spatial information can be represented as stable patterns in a dynamical system. We describe a model in which category perception arises from the incremental recognition of temporal patterns from sequences of inputs and this is accomplished by decoding a pool of recurrently connected artificial neurons which is called a neural field. In an example application, we use these patterns to identify a set of words which share the word onset represented by the input sequence, consistent with the Marslen-Wilson COHORT model of word recognition. Similarly, we evaluate the extent to which information contained in the bottom-up sensory signal can be used to determine word boundaries. We suggest it is plausible that a neural field offers a naturalistic explanation of how perception arises in word processing.

In Their Own Words: A Companion Robot for Detecting the Emotional State of Persons with Parkinson's Disease

In typical human interactions emotional states are communicated via a variety of modalities such ... more In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations, as in the case of facial masking in Parkinson’s disease (PD). In these cases, we need to focus the communication and detection of emotions on the reliable modalities, by inferring emotions from what is being said, and compensate for the modalities that are problematic, by having another agent (e.g., a robot) provide the missing facial expressions. We describe the initial development stage of a robot companion that can assist the communication and detection of emotions in interactions where some modalities are totally or partially compromised. Such is the case for people living with Parkinson’s disease.

Data distribution apparatus and method having a data description including information for specifying a time that a data distribution is to occur

Using topic modeling to infer the emotional state of people living with Parkinson’s disease

Emotion expression in a socially assistive robot for persons with Parkinson's disease

Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Emotions are crucial for human social interactions and thus people communicate emotions through a... more Emotions are crucial for human social interactions and thus people communicate emotions through a variety of modalities: kinesthetic (through facial expressions, body posture and gestures), auditory (the acoustic features of speech) and semantic (the content of what they say). Sometimes however, communication channels for certain modalities can be unavailable (e.g., in the case of texting), and sometimes they can be compromised, due to a disorder such as Parkinson's disease (PD) that may aect facial, gestural and speech expressions of emotions. To address this, we developed a prototype for an emoting robot that can detect emotions in one modality, specically in the content of speech, and then express them in another modality, specically through gestures. The system consists of two components: detection and expression of emotions. In this paper we present the development of the expression component of the emoting system. We focus on its dynamical properties that use a spring model for smooth transitions between emotion expressions over time. This novel method compensates for varying utterance frequency and prediction errors coming from the emotion recognition component. We also describe the input the dynamical expression component receives from the emotion detection component, the development and validation of the output comprising of the gestures instantiated in the robot, and the implementation of the system. We present results from a human validation study that shows people perceive the robot gestures, generated by the system, as expressing the emotions in the speech content. Also, we show that people's perceptions of the accuracy of emotion expression is signicantly higher for a mass-spring dynamical system than a system without a mass-spring when specic detection errors are present. We discuss and suggest future developments of the system and further validation experiments. This paper is part of a larger project to develop a prototype for a socially assistive robot for PD persons. The goal is to present the

A Survey of the Neurological Evidence for Language Selection in Bilingual Speech Production

The "hard problem" in speech production is embodied in the cognitive process which selects the si... more The "hard problem" in speech production is embodied in the cognitive process which selects the single, correct word that the speaker intends to utter from among multiple words activated by their shared semantic concept. Bilingual word selection is even harder because of the generally held assumption that concept selection also activates both of the speaker’s languages to an approximately equal extent.
Several competing hypothesis based on behavioral experiments attempt to explain the hard problem were reviewed by Finkbeiner, M., Gollan, T., & Caramazza, A. (2006). The authors suggest none to be entirely correct and that a simpler cognitive mechanism, selection-by-threshold, best explains many of the observed facilitatory and inhibitory cross-language effects. Subsequent research by Kroll et al. (2008) and Golan & Ferreira (2007) suggests that behavioral studies, specifically those that examine asymmetrical language switching costs in and of itself may not reveal the means of lexical selection.
Rather than relying on behavioral studies, more recent research has examined the evidence on the neural basis of language selection which suggests that inhibitory control is required to enable the bilinguals to speak one language alone. This paper seeks to review the research and identify the consensus, if one exists, on the neurological structures that serve as the locus of language selection and control.

A computational model of bilingual inhibitory control in a lexical decision task

Results from empirical studies in bilingual research demonstrate that “code-switching” in biling... more Results from empirical studies in bilingual research demonstrate
that “code-switching” in bilinguals, i.e., the change from
one language to another, comes at a cost. What is still unclear
is the exact nature of the cost. In this paper, we develop
a connectionist model for Green’s Inhibitory Control (IC) hypothesis
for a bilingual lexical decision task (Green, 1998, 74),
which hypothesizes that the cost of switching between two languages
in this task is due to inhibitory forces among different
task schema and word forms. We were able to fit the model to
the empirical data from Von Studnitz and Green (1997, Experiment
1), thus providing a proof-of-concept model that the IC
hypothesis can account for the observed language switching
costs. More extensive, systematic explorations of the model
and its parameters in related but different tasks are, however,
required to determine the extent of the IC applicability.

Additional Information Websites: Company Website RSS feed Interests: Sailing, Singing, Guitar, Cooking, Music, Theatre

Research proposal: Does Visual speech prime recognition of interlingual homophones in Dutch-English bilinguals?

This is a proposal to investigate whether lexical input received by a shared auditory and visual ... more This is a proposal to investigate whether lexical input received by a shared auditory and visual speech process can create a priming effect by making contact with the shared bilingual lexicon and activating overlapping phonological representations, consistent with a non-selective control model such as BIA+ (Dijkstra & van Heuven, 2002). This extends past research which has examined cross-language effects but has not provided lexical input through visual speech. It also extends research which has examined visual speech priming but in a monolingual context. In Experiment 1, response times are measured when bilingual Dutch-English participants are presented with a video recording of a bilingual Dutch-English speaker providing a visual speech (i.e., visual + auditory modes) prime of interlingual homophones. Participants are asked whether a target word is English or a non-word. Interlingual homophones are words that have identical phonology across languages but different meanings. An example is /lief/ which means “sweet” in Dutch and pronounced as /leaf/ in English.

Proposal for: An investigation of balanced bilinguals’ use of code switching in inner speech

Speakers of more than one language, (i.e. bilinguals) may intentionally mix their languages durin... more Speakers of more than one language, (i.e. bilinguals) may intentionally mix their languages during conversation in a phenomenon known as “code switching”. As a line of scholarly inquiry, code switching is generally limited to the context of bilingual conversation. I propose to extend the investigation to include inner speech, which is the voice that is often heard inside one’s head while thinking. One view of inner speech is that it is produced using processes similar to that we use to speak except that no utterances are produced. In another view, Vygotsky (1986) posits that inner speech is a child’s ego-centric speech turned inward in a more compact way. For this project, an inner speech discourse is stimulated within proficient Korean-English and Spanish-English bilingual participant s in an experiment by providing one of Kohlberg’s moral dilemmas accompanied by a series of questions probing their responses. Code switching is primed by providing instructions in their native language (L1); the dilemma and probe questions are provided in English. At several points during each session, the participants will be asked to reflect on which language they use for inner speech and the role the language is playing in answering the probes. From this study, I seek an understanding of whether code switching is a mechanism that bilinguals engage in during inner speech activities, how they use it, and what role it plays. Code switching is an area of active research which could become a lens to examine and understand bilinguals’ non-verbal reasoning processes and inform the methods used to present and teach abstract concepts to bilinguals.

UDL in Higher Education

Universal Design for Learning (UDL) is derived from universal design, a name coined by the archit... more Universal Design for Learning (UDL) is derived from universal design, a name coined by the architect Ronald L. Mace for the concept of designing accessibility into buildings, structures, and places from the onset. However, it was the work of Selwyn Goldsmith (1997) originally published in 1963 that put it into practice, the most significant example being the introduction of the cut curb. UDL was developed at the Center for Applied Special Technologies (CAST) in the 1990s and described in the book by David Rose and Ann Myers (2002). As with universal design, UDL’s objective is to increase access to those who have historically been marginalized, and this includes learners who might be considered to have learning disabilities such as dyslexia, but also includes students who are non-native language speakers, who have cultural differences that conflict with the prevailing culture in the learning environment, or those students whose learning style is not coincident with the prevailing learning processes used in the classroom.