This study evaluated the possible influence of linguistic demands on speech motor control by measuring articulatory movement stability during conditions of increasing grammatical complexity. There were 60 participants in three age groups: 20-30 years, 40-50 years, and 60-70 years, with equal numbers of men and women in each group. These speakers produced 10 repetitions of five different sentence or phrase conditions. These five conditions included two baseline measurements and three sentences of varying complexity. Each complexity condition had an MLU count of 23, word length of 17, syllable length of 25, and contained the phrase open boxes of pompoms. Complexity was measured by node-count and grammatical structure. Lower lip movements during production of the target phrase were used to compute the spatiotemporal index (STI), a measure of lip movement stability over 10 repetitions. It was predicted that STI would be lower (indicating greater stability) in the baseline and low complexity conditions. Comparison of complexity conditions against the baseline-counting condition demonstrated significant differences in the upper lip's STI, displacement, and velocity, as well as in vocal intensity. Speech motor differences between the grammatical complexity levels were minimal and could be attributed to several factors, such as speaking rate or semantic differences. An unexpected finding of this study was the influence of age on speech production. Participants from the 60 year-old group had significantly longer utterance duration, while those from the 20 year-old group had the highest lower lip and jaw STI values. These findings suggest that speech motor control matures even beyond young adulthood and that linguistic complexity does not appear to have a consistent effect on speech movement variables.

Relative clauses are grammatical constructions that are of relevance in both typical and impaired language development. Thus, the accurate identification of these structures in child language samples is clinically important. In recent years, computer software has been used to assist in the automated analysis of clinical language samples. However, this software has had only limited success when attempting to identify relative clauses. The present study explores the development and clinical importance of relative clauses and investigates the accuracy of the software used for automated identification of these structures. Two separate collections of language samples were used. The first collection included 10 children with language impairment, ranging in age from 7;6 to 11;1 (years;months), 10 age-matched peers, and 10 language-matched peers. A second collection contained 30 children considered to have typical speech and language skills and who ranged in age from 2;6 to 7;11. Language samples were manually coded for the presence of relative clauses (including those containing a relative pronoun, those without a relative pronoun and reduced relative clauses). These samples were then tagged using computer software and finally tabulated and compared for accuracy. ANACOVA revealed a significant difference in the frequency of relative clauses containing a relative pronoun but not for those without a relative pronoun nor for reduce relative clauses. None of the structures were significantly correlated with age; however, frequencies of both relative clauses with and without relative pronouns were correlated with mean length of utterance. Kappa levels revealed that agreement between manual and automated coding was relatively high for each relative clause type and highest for relative clauses containing relative pronouns.

This study examined the effects of low dose exposure to a humanoid robot on the social engagement skills of four children with autism during select activities with a familiar adult. Participants included two males and two females who ranged in age from four to nine at the commencement of the study. The current study was part of a larger investigation focused on the effect of exposure to a robot on social engagement with a variety of social partners and situations. Children participated in variable multiple baseline sessions followed by a varied number of sessions of traditional treatment. After traditional treatment, the children participated in 40 minutes of traditional intervention paired with 10 minutes of exposure to a robot designed to elicit social communication skills. The final sessions consisted of follow up assessments. Pre- and posttreatment data were compared and analyzed. Results showed variable performance for each of the participants. Findings and areas of future research are discussed.

Advances in instrumentation and computer technology such as electropalatography (EPG) have offered additional types of feedback to more traditional therapy for individuals with speech disorders, specifically those with hearing impairment. The purpose of this study was to document whether therapeutic integration of EPG visual feedback in combination with traditional articulation therapy for a school-aged child with an articulation disorder secondary to hearing impairment was more effective than traditional therapy alone. One participant received five sessions of each therapy approach. Six adult listeners rated the quality of the participant's production of /r/ in words recorded during the therapy sessions. The EPG plus a traditional approach to therapy was more effective in treating the misarticulation of /r/ than traditional therapy alone. The integration of EPG therapy into traditional methods was an effective way of treating an articulation disorder for an individual with hearing impairment.

This study is a small portion of a larger work examining the effects of low dosage robot use in interactive and social engagement therapy for children with autism. The purpose of this study was to investigate the participation of the subjects during song activities. Four children were used as participants, each receiving a total of 20 play-based treatment sessions targeting engagement and social interaction. The clinician incorporated the robot into these treatment sessions for 10 minute long segments within a 50 minute session. The current study analyzed these 10 minute segments with the robot, coding turn-taking behaviors. Results indicated that, at least for a time, the robot facilitated improvement in these behaviors for two of the four children. The other two children demonstrated no improvements. These results are discussed, and the limitations of the study and recommendations for future research are examined.

The current study was part of a larger work investigating the effects of intervention incorporating a robot on the social engagement behaviors of children with autism. The larger study implemented a single-subject, multiple-baseline research design in which four children with autism participated in baseline sessions, traditional intervention, intervention including a robot, and follow-up sessions. The current study focused on the participant's responses to directives from the clinician and the parent during collaborative activities that included the robot. Children's responses were analyzed to determine if they responded to directives without assistance, responded with hand-over-hand assistance, or did not comply. Sessions were complex and required the development of a detailed analysis system to ensure fidelity. Overall results were highly variable but showed gains in one child. Clinical observation suggested that all four children benefited from their exposure to the robot, particularly with regards to regulation. Although variable, the results of this study suggest potential for the promotion and generalization of a child's ability to respond to social engagement bids with other humans. Additional research should be conducted to establish the effectiveness of a robot in intervention in generalizing social engagement behaviors in children with autism.

By the later preschool years, most children have a knowledge of the grammatical categories of their native language and are capable of expanding this knowledge to novel words. To model this accomplishment, researchers have created a variety of explicit, testable models or algorithms. These have had partial but promising success in extracting grammatical word categories from transcriptions of caregiver input to young children. Additional insight into children's learning of the grammatical categories of words might be gained from evolutionary computing algorithms, which apply principles of evolutionary biology such as variation, adaptive change, self-regulation, and inheritance to computational models. The current thesis applied such a model to the language addressed to five children, whose ages ranged from 1;1 to 5;1 (years;months). The model evolved dictionaries linking words to their grammatical tags and was run for 4000 cycles; four different rates of mutation of offspring dictionaries were assessed. The accuracy for coding the words in the corpora of language addressed to the children averaged 92.74%. Directions for further development and evaluation of the model are proposed.

Previous research has investigated adults' ability to adapt their speech when a electropalatographic (EPG) pseudopalate is placed in the oral cavity; however, less is known about how younger speakers who are continuing to develop their motor speech abilities might adapt their speech to the presence of the device. This study examined the effect of an EPG pseudopalate on elementary school-aged children's ability to produce the fricatives /s/ and /ƒ/. Audio recordings of six children were collected at eight time intervals including before placement of the pseudopalate, at 30-minute increments for two hours with the pseudopalate in place, immediately following removal of the pseudopalate and 30 minutes after removal. An acoustic analysis was completed looking at consonant duration, spectral mean, spectral variance, and relative intensity. Disturbance of speech patterns from the presence of the pseudopalate was noted for most of the acoustic measures, most noticeably for the relative intensity of both /s/ and /ƒ/, as well as for the spectral mean and spectral variance of /ƒ/. Although there was a relatively high amount of variability among and within speakers, signs of adaptation were apparent after only 30 minutes for some participants. For some acoustic measures, however, full adaptation often did not occur until the pseudopalate was removed. Although future research is needed, it is hoped that this study will provide a greater understanding of children's ability to adapt to the EPG pseudopalate.

Most children who follow a typical developmental timeline learn the grammatical categories of words in their native language by the time they enter school. Researchers have worked to provide a number of explicit, testable models or algorithms in an attempt to model this language development. These models or algorithms have met with some varying success in terms of determining grammatical word categories from the transcripts of adult input to children. A new model of grammatical category acquisition involving an application of evolutionary computing algorithms may provide further understanding in this area. This model implements aspects of evolutionary biology, such as variation, adaptive change, self-regulation, and inheritance. The current thesis applies this model to six English language corpora. The model created dictionaries based on the words in each corpus and matched the words with their grammatical tags. The dictionaries evolved over 5,000 generations. Four different mutation rates were used in creating offspring dictionaries. The accuracy achieved by the model in correctly matching words with tags reached 90%. Considering this success, further research involving an evolutionary model appears warranted.

Most typically developing children have achieved a knowledge of the grammatical categories of the words in their native language by school age. To model this achievement, researchers have developed a variety of explicit, testable models or algorithms which have had partial but promising success in extracting the grammatical word categories from the transcriptions of caregiver input to children. Additional insight into children's learning of the grammatical categories of words might be obtained from an application of evolutionary computing algorithms, which simulate principles of evolutionary biology such as variation, adaptive change, self-regulation, and inheritance. Thus far, however, this approach has only been applied to English language corpora. The current thesis applied such a model to corpora of language addressed to five Spanish-speaking children, whose ages ranged from 0;11 to 4;8 (years; months). The model evolved dictionaries which linked words to their grammatical tags and was run for 5000 cycles; four different rates of mutation of offspring dictionaries were assessed. The accuracy for coding the words in the corpora of language addressed to the children peaked at about 85%. Directions for further development and evaluation of the model and its application to Spanish language corpora are suggested.