The LTA project: Bridging the gap between training and the profession in real-time intralingual subtitling

Real-time intralingual subtitles enable access to live audiovisual products. However, the provision and the quality of such services across Europe is uneven and sometimes insufficient because live subtitlers are untrained or only partially trained and without recognized professional status. To bridge this gap, the EU-funded project Live Text Access (LTA) aims to create ad-hoc training materials and propose the recognition of certified professionals. This article first concentrates on the multifaceted and heterogeneous terminology adopted in the field. Then it provides an overview of the current situation in which live subtitlers are trained in Europe, focusing on the LTA rationale for creating open-source training materials based on certification, subtitling standards and a user-oriented approach. Finally, it reports on the progress the project has made in defining both the professional profile and the skills and competences of the intralingual real-time subtitler

Comparative analysis between a respeaking captioning system and a captioning system without human intervention

People living with deafness or hearing impairment have limited access to information broadcast live on television. Live closed captioning is a currently active area of study; to our knowledge, there is no system developed thus far that produces high-quality captioning results without using scripts or human interaction. This paper presents a comparative analysis of the quality of captions generated for four Spanish news programs by two captioning systems: a semiautomatic system based on respeaking (system currently used by a Spanish TV station) and an automatic system without human interaction proposed and developed by the authors. The analysis is conducted by measuring and comparing the accuracy, latency and speed of the captions generated by both captioning systems. The captions generated by the system presented higher quality considering the accuracy in terms of Word Error Rate (WER between 3.76 and 7.29%) and latency of the captions (approximately 4 s) at an acceptable speed to access the information. We contribute a first study focused on the development and analysis of an automatic captioning system without human intervention with promising quality results. These results reinforce the importance of continuing to study these automatic systems

Efficacy of Community Education Programmes in Influencing Public Reception and Response Behaviour Factors Related to Tornado Warning Systems

The thesis explores the U.S. early warning system in the context of three separate but interlocking components: emergency management; special needs populations, in this case represented by the Deaf and hard of hearing community; and disaster education. Of importance is the need to bring further understanding to the relevancy of each and how the interrelationship among all three reflects a microcosm illustrative of the larger early warning paradigm and its challenges. Meeting those challenges requires implementation of innovative interventions and evidence-based approaches for adapting to the changing urban and rural demographics, climatological and technological environments. Severe weather and tornado hazard early warning is the embodiment of an integration of multiple systems requiring complex coordination of functions consisting of forecasting, detection, analysis, message development and dissemination, message reception, and action. This culminates in individual decision making for taking self-protection measures. The thesis methodological framework consisted of a mixed method approach. Data collection utilised a survey questionnaire instrument, individual interviews and focus groups. The research questioned if current warning processes within the U.S. tornado early warning system positively integrate with emergency management practices and effectively influence protective actions of the special needs population. Results indicate the emergency management system continues to be institutionally focused and operationally centric. Emergency managers recognise the need to become more of an integrated component between the warning mechanism and the communities they represent. Data indicate the Deaf and hard of hearing population remains underserved and generally ill-prepared for severe weather events. Disaster education programmes addressing their particular needs are scarce and current warning notification processes are often inadequate. Although tornado early warning detection and notification times are increasing, questions remain on how to more effectively encourage individuals to better heed warning messages

Dynamic language modeling for European Portuguese

Doutoramento em Engenharia InformáticaActualmente muitas das metodologias utilizadas para transcrição e indexação de transmissões noticiosas são baseadas em processos manuais. Com o processamento e transcrição deste tipo de dados os prestadores de serviços noticiosos procuram extrair informação semântica que permita a sua interpretação, sumarização, indexação e posterior disseminação selectiva. Pelo que, o desenvolvimento e implementação de técnicas automáticas para suporte deste tipo de tarefas têm suscitado ao longo dos últimos anos o interesse pela utilização de sistemas de reconhecimento automático de fala. Contudo, as especificidades que caracterizam este tipo de tarefas, nomeadamente a diversidade de tópicos presentes nos blocos de notícias, originam um elevado número de ocorrência de novas palavras não incluídas no vocabulário finito do sistema de reconhecimento, o que se traduz negativamente na qualidade das transcrições automáticas produzidas pelo mesmo. Para línguas altamente flexivas, como é o caso do Português Europeu, este problema torna-se ainda mais relevante. Para colmatar este tipo de problemas no sistema de reconhecimento, várias abordagens podem ser exploradas: a utilização de informações específicas de cada um dos blocos noticiosos a ser transcrito, como por exemplo os scripts previamente produzidos pelo pivot e restantes jornalistas, e outro tipo de fontes como notícias escritas diariamente disponibilizadas na Internet. Este trabalho engloba essencialmente três contribuições: um novo algoritmo para selecção e optimização do vocabulário, utilizando informação morfosintáctica de forma a compensar as diferenças linguísticas existentes entre os diferentes conjuntos de dados; uma metodologia diária para adaptação dinâmica e não supervisionada do modelo de linguagem, utilizando múltiplos passos de reconhecimento; metodologia para inclusão de novas palavras no vocabulário do sistema, mesmo em situações de não existência de dados de adaptação e sem necessidade re-estimação global do modelo de linguagem.Most of today methods for transcription and indexation of broadcast audio data are manual. Broadcasters process thousands hours of audio and video data on a daily basis, in order to transcribe that data, to extract semantic information, and to interpret and summarize the content of those documents. The development of automatic and efficient support for these manual tasks has been a great challenge and over the last decade there has been a growing interest in the usage of automatic speech recognition as a tool to provide automatic transcription and indexation of broadcast news and random and relevant access to large broadcast news databases. However, due to the common topic changing over time which characterizes this kind of tasks, the appearance of new events leads to high out-of-vocabulary (OOV) word rates and consequently to degradation of recognition performance. This is especially true for highly inflected languages like the European Portuguese language. Several innovative techniques can be exploited to reduce those errors. The use of news shows specific information, such as topic-based lexicons, pivot working script, and other sources such as the online written news daily available in the Internet can be added to the information sources employed by the automatic speech recognizer. In this thesis we are exploring the use of additional sources of information for vocabulary optimization and language model adaptation of a European Portuguese broadcast news transcription system. Hence, this thesis has 3 different main contributions: a novel approach for vocabulary selection using Part-Of-Speech (POS) tags to compensate for word usage differences across the various training corpora; language model adaptation frameworks performed on a daily basis for single-stage and multistage recognition approaches; a new method for inclusion of new words in the system vocabulary without the need of additional data or language model retraining

Implications for CALL: Teachers’ Perceptions and Use of CALL in the Classroom

Abstract The goal of this study was to ascertain graduate students’ perceptions of technology use in language learning classroom. More specifically it sought to find out how the graduate students perceived technology, how technologically savvy they felt they were, and how they actually use technology and Computer Assisted Language Learning in their classrooms. A survey was conducted with 14. From those 14 participants, 4 individuals volunteered to take part in an interview to answer questions pertaining to their philosophy about technology, when it is beneficial to language learning, when it is detrimental to language learning, and how technologically adept they feel they are concerning technology and how that drives their use of it in their classroom. The survey is broken down into three sections. Section I focused on the collection of demographic information through 11 open questions and 5 closed Yes/No questions. Section II was comprised of two closed yes/no questions as well as 4 open questions pertaining to whether the participants have used a computer to learn a language. Section III consists of 94 Likert questions that participants can mark their answer as 1-6 with 1=Strongly Agree, 2=Agree, 3=Slightly Agree, 4= Slightly Disagree, 5= Disagree, 6=Strongly Disagree. Within Section III the questions can be attributed to three different categories: Perception of computers and technology, instructor affinity for computers and technology, and instructor’s use of computers and technology in the classroom. Results show that instructors have a favorable view of technology, a slightly lower view of their personal affinity for technology, and a favorable view of technology use within their classrooms. Keywords: CALL, CAI, Computer Assisted Language Learning, teacher perceptions, technology use in the classroo

Future of Online and Digital Learning in Post-Secondary Art Institutions

This research project explores the current state of online and digital learning in Post-Secondary Art (PSA) institutions and highlights some of the key challenges and opportunities for change within an institution. The paper aims to visualize possible future scenarios for learning in art institutions and provide recommendations to assist in planning for the future of these organizations. The project draws on the theories of learning, a history of transformation in higher education, elements of online learning, and current trends in the field, to build a foundation for possible futures. By using foresight methodologies, the project generates four scenarios that take readers to 2040 and provide them with alternative learning landscapes through technology

Embracing the threat: machine translation as a solution for subtitling

Recent decades have brought significant changes in the subtitling industry, both in terms of workflow and in the context of the market for audiovisual translation. Machine translation (MT), whilst in regular use in the traditional localisation industry, has not seen a significant uptake in the subtitling arena. The SUMAT project, an EU-funded project which ran from 2011 to 2014 had as its aim the building and evaluation of viable MT solutions for the subtitling industry in nine bidirectional language pairs. As part of the project, a year-long large-scale evaluation of the output of the resulting MT engines was carried out by trained subtitlers. This paper reports on the impetus behind the investigation of MT for subtitling, previous work in this field, and discusses some of the results of this evaluation, in particular an attempt to measure the extent of productivity gain or loss for subtitlers using machine translation as opposed to working in the traditional way. The paper examines opportunities and limitations of MT as a viable option for work of this nature and makes recommendations for the training of subtitle post-editors