Contact, Mobility and Authenticity: Language Ideologies in Koineisation and Creolisation

Part II - Christoph Neuenschwander: Language ideologies in the legitimisation of Tok Pisin as a lingua franca Pidgins and Creoles all over the world seem to share common aspects in the historical circumstances of their genesis and evolution. They all emerged in the context of colonialism, in which not only colonisers and colonised, but also the various groups of the colonised population spoke different languages. Pidgins and Creoles, quite simply, resulted from the need to communicate.¬¬ Yet, the degree to which they became accepted as a lingua franca or in fact even as a linguistic variety in its own right, strikingly differs from variety to variety. The current research project focuses on two Pacific Creoles: Tok Pisin, spoken on Papua New Guinea, and Hawai'i Creole English (HCE). Whereas Tok Pisin is a highly stabilised and legitimised variety, used as a lingua franca in one of the most linguistically diverse countries on Earth, HCE seems to be regarded as nothing more than broken English by a vast majority of the Hawai'ian population. The aim of this project is to examine the metalinguistic comments about both varieties and to analyse the public discourses, in which the status of Tok Pisin and HCE were and still are negotiated. More precisely, language ideologies shall be identified and compared in the two contexts. Ultimately, this might help us understand the mechanisms that underlie the processes of legitimisation or stigmatisation. As Laura Tresch will run a parallel research project on language ideologies on new dialects (New Zealand English and Estuary English), a comparison between the findings of both projects may produce even more insights into those mechanisms. The next months of the project will be dedicated to investigating the metalinguistic discourse in Papua New Guinea. In order to collect a wide range of manifestations of language ideologies, i.e. instances of (lay and academic) commentary on Tok Pisin, it makes sense to look at a relatively large period of time and to single out events that are likely to have stimulated such manifestations. In the history of Papua New Guinea - and in the history of Tok Pisin, in particular - several important social and political events concerning the use and the status of the language can be detected. One example might be public debates on education policy. The presentation at the CSLS Winter School 2014 will provide a brief introduction to the history of Tok Pisin and raise the methodological question of how to spot potential sites of language-ideological production.

Patrol team language identification system for DARPA RATS P1 evaluation

This paper describes the language identification (LID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We show that techniques originally developed for LID on telephone speech (e.g., for the NIST language recognition evaluations) remain effective on the noisy RATS data, provided that careful consideration is applied when designing the training and development sets. In addition, we show significant improvements from the use of Wiener filtering, neural network based and language dependent i-vector modeling, and fusion.

Phonotactic language recognition using i-vectors and phoneme posteriogram counts

This paper describes a novel approach to phonotactic LID, where instead of using soft-counts based on phoneme lattices, we use posteriogram to obtain n-gram counts. The high-dimensional vectors of counts are reduced to low-dimensional units for which we adapted the commonly used term i-vectors. The reduction is based on multinomial subspace modeling and is designed to work in the total-variability space. The proposed technique was tested on the NIST 2009 LRE set with better results to a system based on using soft-counts (Cavg on 30s: 3.15% vs 3.43%), and with very good results when fused with an acoustic i-vector LID system (Cavg on 30s acoustic 2.4% vs 1.25%). The proposed technique is also compared with another low dimensional projection system based on PCA. In comparison with the original soft-counts, the proposed technique provides better results, reduces the problems due to sparse counts, and avoids the process of using pruning techniques when creating the lattices.

A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology.

Evaluating a web-based clinical decision support system for language disorders screening in a nursery school

Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods: This paper details the evaluation results of the ?Gades? CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child?s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results: The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address these issues and include the requested improvements, with the support of the experts who took part in the original KB development. Conclusions: This research demonstrated the benefit of a Web-based CDSS to monitor children?s neurodevelopment via the early detection of language delays at a nursery school. Current next steps focus on the design of a model that includes pseudo auto-learning capacity, supervised by experts.