Information flow, artificial phonology and typology

In the context Artificial Grammar Learning (AGL) experiments, it is possible to quantify how effectively a stimulus has conveyed information and specifically the information the experimenter thinks it was designed to convey. At the most basic level, this can be done if one has access to the response variability of independent responses to the same stimulus (or subparts of the stimulus). The variability of these responses serves as an index of the amount of information that flows from the source of the stimulus to the perceiver. Quantifying information flow in this way, it is shown that under conditions where participants learn a ‘natural’ but not an ‘unnatural’ rule there are asymmetries in entropic quantities under the different conditions

Diagnostic evaluation in linguistic word recognition

This report is concerned with a new method of evaluation for the Linguistic Word Recognition component of the Verbmobil-Project: Architektur. A two stage model of diagnostic evaluation is presented consisting of logical and empirical evaluation steps. Logical evaluation is carried out according to a data model which acts as optimal input in order that each component participating in the evaluation process can be tested for soundness and completeness. Inconsistencies can thus be remedied before empirical evaluation of the model is undertaken using real data. The diagnostic evaluation method has been operationalised within the Bielefeld Extended Evaluation Toolkit for Lattices of Events (BEETLE)

LESSONS LEARNED AFTER DEVELOPMENT AND USE OF A DATA COLLECTION APP FOR LANGUAGE DOCUMENTATION (LIG-AIKUMA)

International audienceLig-Aikuma is a free Android app running on various mobile phones and tablets. It proposes a range of different speech collection modes (recording, respeaking, translation and elicitation) and offers the possibility to share recordings between users. More than 250 hours of speech in 6 different languages from sub-Saharan Africa (including 3 oral languages in the process of being documented) have already been collected with Lig-Aikuma. This paper presents the lessons learned after 3 years of development and use of Lig-Aikuma. While significant data collections were conducted, this has not been done without difficulties. Some mixed results lead us to stress the importance of design choices, data sharing architecture and user manual. We also discuss other potential uses of the app, discovered during its deployment: data collection for language revitalisation, data collection for speech technology development (ASR) and enrichment of existing corpora through the addition of spoken comments

Neural Network Prognostics Model for Industrial Equipment Maintenance

This paper presents a new prognostics model based on neural network technique for supporting industrial maintenance decision. In this study, the probabilities of failure based on the real condition equipment are initially calculated by using logistic regression method. The failure probabilities are subsequently utilized as input for prognostics model to predict the future value of failure condition and then used to estimate remaining useful lifetime of equipment. By having a time series of predicted failure probability, the failure distribution can be generated and used in the maintenance cost model to decide the optimal time to do maintenance. The proposed prognostic model is implemented in the industrial equipment known as autoclave burner. The result from the model reveals that it can give prior warnings and indication to the maintenance department to take an appropriate decision instead of dealing with the failures while the autoclave burner is still operating. This significant contribution provides new insights into the maintenance strategy which enables the use of existing condition data from industrial equipment and prognostics approach

Sign and speech share partially overlapping conceptual representations

Conceptual knowledge is fundamental to human cognition. Yet the extent to which it is influenced by language is unclear. Studies of semantic processing show that similar neural patterns are evoked by the same concepts presented in different modalities (e.g. spoken words and pictures or text) [1–3]. This suggests that conceptual representations are ‘modality independent’. However, an alternative possibility is that the similarity reflects retrieval of common spoken language representations. Indeed, in hearing spoken language users, text and spoken language are co-dependent [4,5] and pictures are encoded via visual and verbal routes [6]. A parallel approach investigating semantic cognition, shows that bilinguals activate similar patterns for the same words in their different languages [7,8]. This suggests that conceptual representations are ‘language independent’. However, this has only been tested in spoken language bilinguals. If different languages evoke different conceptual representations, this should be most apparent comparing languages that differ greatly in structure. Hearing people with signing deaf parents are bilingual in sign and speech: languages conveyed in different modalities. Here we test the influence of modality and bilingualism on conceptual representation by comparing semantic representations elicited by spoken British English and British Sign Language in hearing early, sign-speech bilinguals. We show that representations of semantic categories are shared for sign and speech, but not for individual spoken words and signs. This provides evidence for partially shared representations for sign and speech, and shows that language acts as a subtle filter through which we understand and interact with the world

Methods in prosody

This book presents a collection of pioneering papers reflecting current methods in prosody research with a focus on Romance languages. The rapid expansion of the field of prosody research in the last decades has given rise to a proliferation of methods that has left little room for the critical assessment of these methods. The aim of this volume is to bridge this gap by embracing original contributions, in which experts in the field assess, reflect, and discuss different methods of data gathering and analysis. The book might thus be of interest to scholars and established researchers as well as to students and young academics who wish to explore the topic of prosody, an expanding and promising area of study