Development of Automatic Speech Recognition for the Documentation of Cook Islands Māori

This paper describes the process of data processing and training of an automatic speech recognition (ASR) system for Cook Islands Māori (CIM), an Indigenous language spoken by approximately 22,000 people in the South Pacific. We transcribed four hours of speech from adults and elderly speakers of the language and prepared two experiments. First, we trained three ASR systems: one statistical, Kaldi; and two based on Deep Learning, DeepSpeech and XLSR-Wav2Vec2. Wav2Vec2 tied with Kaldi for lowest character error rate (CER=6±1) and was slightly behind in word error rate (WER=23±2 versus WER=18±2 for Kaldi). This provides evidence that Deep Learning ASR systems are reaching the performance of statistical methods on small datasets, and that they can work effectively with extremely low-resource Indigenous languages like CIM. In the second experiment we used Wav2Vec2 to train models with held-out speakers. While the performance decreased (CER=15±7, WER=46±16), the system still showed considerable learning. We intend to use ASR to accelerate the documentation of CIM, using newly transcribed texts to improve the ASR and also generate teaching and language revitalization materials. The trained model is available under a license based on the Kaitiakitanga License, which provides for non-commercial use while retaining control of the model by the Indigenous community.falseMarseille, Franc

A computational model for studying L1’s effect on L2 speech learning

abstract: Much evidence has shown that first language (L1) plays an important role in the formation of L2 phonological system during second language (L2) learning process. This combines with the fact that different L1s have distinct phonological patterns to indicate the diverse L2 speech learning outcomes for speakers from different L1 backgrounds. This dissertation hypothesizes that phonological distances between accented speech and speakers' L1 speech are also correlated with perceived accentedness, and the correlations are negative for some phonological properties. Moreover, contrastive phonological distinctions between L1s and L2 will manifest themselves in the accented speech produced by speaker from these L1s. To test the hypotheses, this study comes up with a computational model to analyze the accented speech properties in both segmental (short-term speech measurements on short-segment or phoneme level) and suprasegmental (long-term speech measurements on word, long-segment, or sentence level) feature space. The benefit of using a computational model is that it enables quantitative analysis of L1's effect on accent in terms of different phonological properties. The core parts of this computational model are feature extraction schemes to extract pronunciation and prosody representation of accented speech based on existing techniques in speech processing field. Correlation analysis on both segmental and suprasegmental feature space is conducted to look into the relationship between acoustic measurements related to L1s and perceived accentedness across several L1s. Multiple regression analysis is employed to investigate how the L1's effect impacts the perception of foreign accent, and how accented speech produced by speakers from different L1s behaves distinctly on segmental and suprasegmental feature spaces. Results unveil the potential application of the methodology in this study to provide quantitative analysis of accented speech, and extend current studies in L2 speech learning theory to large scale. Practically, this study further shows that the computational model proposed in this study can benefit automatic accentedness evaluation system by adding features related to speakers' L1s.Dissertation/ThesisDoctoral Dissertation Speech and Hearing Science 201

Computer lipreading via hybrid deep neural network hidden Markov models

Constructing a viable lipreading system is a challenge because it is claimed that only 30% of information of speech production is visible on the lips. Nevertheless, in small vocabulary tasks, there have been several reports of high accuracies. However, investigation of larger vocabulary tasks is rare. This work examines constructing a large vocabulary lipreading system using an approach based-on Deep Neural Network Hidden Markov Models (DNN-HMMs). We present the historical development of computer lipreading technology and the state-ofthe-art results in small and large vocabulary tasks. In preliminary experiments, we evaluate the performance of lipreading and audiovisual speech recognition in small vocabulary data sets. We then concentrate on the improvement of lipreading systems in a more substantial vocabulary size with a multi-speaker data set. We tackle the problem of lipreading an unseen speaker. We investigate the effect of employing several stepstopre-processvisualfeatures. Moreover, weexaminethecontributionoflanguage modelling in a lipreading system where we use longer n-grams to recognise visual speech. Our lipreading system is constructed on the 6000-word vocabulary TCDTIMIT audiovisual speech corpus. The results show that visual-only speech recognition can definitely reach about 60% word accuracy on large vocabularies. We actually achieved a mean of 59.42% measured via three-fold cross-validation on the speaker independent setting of the TCD-TIMIT corpus using Deep autoencoder features and DNN-HMM models. This is the best word accuracy of a lipreading system in a large vocabulary task reported on the TCD-TIMIT corpus. In the final part of the thesis, we examine how the DNN-HMM model improves lipreading performance. We also give an insight into lipreading by providing a feature visualisation. Finally, we present an analysis of lipreading results and suggestions for future development

Spartan Daily, February 19, 1996

Volume 106, Issue 17https://scholarworks.sjsu.edu/spartandaily/8802/thumbnail.jp

Spartan Daily, February 19, 1996

Volume 106, Issue 17https://scholarworks.sjsu.edu/spartandaily/8802/thumbnail.jp

The Art of Un-belonging

This practice-based research sets out to explore artistic strategies that destabilise fixed notions of belonging and identity in the context of globalisation and diasporic art. Drawing on Glissant’s concept of Relation ([1990], 1997) in combination with feminist and new materialist theories (Braidotti, Haraway) and an “anthropology beyond the human” (Kohn, 2013), the research challenges a dualistic conception of self/Other and contributes to the decolonisation of contemporary art by opening and reinscribing the concept of belonging and identity beyond the human. The practice element consists of three discrete yet interrelated artworks that challenge an ethnocentric and anthropocentric conception of belonging. The multilingual video-performance Surya Namaz (2018) is a personal investigation of yoga and namaz, the Muslim prayer ritual, exploring the potential of transcultural performance, opacity and multilingualism to undo fixed notions of belonging. Kahvehane Kongresspark (2016), a temporary café, ceramic cups/saucers and a site-specific performance in public space and Trans Plantations (2018), an installation of cups/saucers and coffee beans cast in porcelain in combination with an audio-visual element, are concerned with the colonial history and human entanglements with coffee, taking the exploration of belonging beyond the anthropocentric. The written thesis is composed of three chapters. Chapter 1 contextualises the research by providing a brief overview on the globalisation of art and introduces Glissant’s theory of Relation as guiding framework of the thesis. This part also reflects on feminist art and theory’s relevance for current discourses concerned with belonging and identity, exploring the potential of feminist strategies for the complication of binary thinking. The subsequent chapters are guided by and complement the practice element of the thesis through ways of critical analysis and performative writing, addressing questions posed by the practice in addition to case studies of contemporary artworks. Based on the conception of identity as relational, the research argues that Relation is central to the re-thinking of belonging and identity

Project-Based Learning in Introductory Psychology: Modern Adaptations To an Academic Classic

This study used a quasi-experimental design to examine the effectiveness of a project-based learning (PjBL) course design on meaningful learning, student goal orientation, engagement, and perceived classroom motivational climate in an introductory psychology course. Project-based learning was examined in comparison to a traditional, lecture and multiple-choice exam course design in introductory psychology over the course of one semester (N = 247). Generally, there is limited research examining PjBL in large introductory classes, specifically in relation to concrete outcomes such as meaningful learning and perceived classroom climate (Gurung et al., 2016). Therefore, the purpose of the study was to add to the limited research that exists and work to encourage the use of alternative designs like PjBL in large introductory courses. I decided to employ a PjBL design in introductory psychology because it is a course that has remained generally unchanged in the last few decades. It typically involves large class sizes, daily lectures, minimal active learning opportunities, and multiple-choice exams once every four weeks. I believe it has become a “classic” as defined by John Dewey (Dewey, 1933). It has become something that people no longer find true wonder or intrigue in and simply recognize it as existing in one way. As an introductory psychology instructor, I quickly realized the affordances of the course and felt the traditionally accepted format was not maximizing these students’ potential benefits. The research that does exist related to PjBL and introductory courses (i.e., Hard et al., 2018) and research that speaks to the power of introductory psychology in general (i.e., Gurung et al., 2016) encouraged me to pursue alternative methods and examine their potential benefits related to valuable academic outcomes such meaningful learning, goal orientation, engagement, and classroom motivational climate. Findings from the current study yielded no statistically significant differences between the PjBL condition and traditional condition regarding meaningful learning, goal orientation, or engagement (measured through transformative experience), suggesting that other motivational and learning outcomes may want to be examined. However, significant differences were found when examining perceived classroom motivational climate. These differences are in line with existing motivational climate research (i.e., Appleton et al., 2016; Dweck & Leggett, 1988) and speak to the potential value of authentic, autonomy-supportive course designs in improving student climate perceptions

Development and Implementation of the Midwest Geological Sequestration Consortium CO2-Technology Transfer Center

In 2009, the Illinois State Geological Survey (ISGS), in collaboration with the Midwest Geological Sequestration Consortium (MGSC), created a regional technology training center to disseminate carbon capture and sequestration (CCS) technology gained through leadership and participation in regional carbon sequestration projects. This technology training center was titled and branded as the Sequestration Training and Education Program (STEP). Over the last six years STEP has provided local, regional, national, and international education and training opportunities for engineers, geologists, service providers, regulators, executives, K-12 students, K-12 educators, undergraduate students, graduate students, university and community college faculty members, and participants of community programs and functions, community organizations, and others. The goal for STEP educational programs has been on knowledge sharing and capacity building to stimulate economic recovery and development by training personnel for commercial CCS projects. STEP has worked with local, national and international professional organizations and regional experts to leverage existing training opportunities and provide stand-alone training. This report gives detailed information on STEP activities during the grant period (2009-2015).Department of Energy Agreement DE-FE0002462Ope

Washington University Magazine, October 2010

https://digitalcommons.wustl.edu/ad_wumag/1193/thumbnail.jp