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Among the most important sociocultural phenomena of contemporary global societies, immigration brings significant changes to all areas of immigrants' life (family, profession, and quality of life), impacting their cultural identities, including identity associated with their language use. As migrants need to be understood in the languages they are proficient in, receive instruction in the destination language, and access essential services understandable to them, language becomes an indispensable agent of migration. In this context, our paper examines the impact of migration on the linguistic behaviour of immigrants, and recognising the pivotal role of language in facilitating the integration of immigrants into host societies. The study focuses on the circumstances Romanian immigrants within Belgium's multilingual milieu, illustrating the dimensions of the identity crisis they grapple with. Data analysis has shown that migration generates consistent changes regarding the immigrants' linguistic behaviour, driven, on the one hand, by their desire to be integrated in the host country and, on the other hand, by their attachment to the cultural heritage values of their country of origin. [ABSTRACT FROM AUTHOR]

This paper presents the first dialectometric analysis of intonational variation of standard spoken Romanian. The data analysed (26,680 sentences) were gathered within the AMPER-ROM project and the dialectometrical analysis has been carried out with ProDis. The results are consistent with the geolinguistic descriptions of Romanian varieties. ProDis identified two major areas for yes-no questions: a central-eastern one (Moldo-Walachian), with rising contours, and a central-western one (Transylvanian, discontinuously continuing over Bukovina to Bessarabia--the Republic of Moldova--), which presents also falling contours. The study suggests that intonational areas are somehow more conservative of and (relatively) independent from segmental dialectal areas. [ABSTRACT FROM AUTHOR]

This paper focuses on an analysis of the intonation patterns of different types of vocatives in Romanian language. We present the main characteristics of the tonal patterns observed in the vocative constructions instances of isolated vocatives and contexts in which vocatives occur in different positions: initial, middle, and final. Our analysis, in the framework of AM phonology with ToBI conventions, reveals that most of isolated vocatives are realized as LsH*(!)H% (vocative chant), and L+H* L% (insistent call). For non-isolated vocatives the most frequent contours are labeled as L+H* L% and H+L* L%. Cross-linguistically, our findings show that Romanian vocatives display the same pattern as other Romance languages. [ABSTRACT FROM AUTHOR]

The aim of this paper is to classify Romanian dialects from a prosodic point of view within the European Romance-speaking area. The data is part of the Multimedia Atlas of Romance Prosody - AMPER (Contini, 1992) and is analysed dialectometrically by means of ProDis (Elvira-García et al., 2015; Fernández Planas, 2016). The database includes more than 17,000 utterances produced by 48 speakers from 26 survey sites of 15 varieties of 6 Romance languages (Catalan, Spanish, Italian, Sardinian, Friulian and Romanian). The results show that the two main prosodic areas of Romanian (see Roseano, 2016b) remain separate when they are dialectometrized with data from other Romance languages. In addition, if one analyses questions and statements separately, it can be seen that questions allow us to distinguish geoprosodic areas more effectively than statements do (as suggested by previous studies such as Fernández Planas et al., 2015). [ABSTRACT FROM AUTHOR]

The article discusses about the Special Issue Current Approaches to Romanian and Spanish Intonation with focuses on Prosodic distances between different survey sites in Romance-speaking Europe, a dialectometric approach to Romanian intonation.and Some considerations about intonation patterns of vocatives in Romanian language.

Research and innovation play a key role in generating smart and sustainable economic growth. By producing new knowledge, the research contributes to the development of new and innovative products, processes, and services, which in turn lead to increased productivity, industrial competitiveness, and, ultimately, the prosperity of the community as a whole. However, all research, development and innovation activities depend on the financial resources made available, as specific financing accelerates the production and dissemination of the best ideas and practices, as well as their role in meeting the challenges our society deals with nowadays. Our study aims to identify the determining factors for the researcher's participation and success rates in research funding competitions. The goal of the research is to understand how variables such as age, gender, main field, affiliation, and scientific rank can affect the access to funding opportunities available for research and innovation. The study relies on a questionnaire-based survey conducted with 243 early-career and senior researchers from many state universities across Romania. For an in-depth analysis of the factors that influence the success rate in research competitions, in the present approach, we used both graphical and econometric methods. A binary logistic regression modelling was performed in order to explain the relationships between variables. Among other considerations, our findings revealed that in all main research fields, scientific rank and gender are important features for raising the participation and success rate in research funding competitions. [ABSTRACT FROM AUTHOR]

Automatic speech segmentation has many applications in speech processing and phonetics, e.g., in automatic speech recognition and automatic annotation of speech corpora. In both processes of training and evaluation of speech recognition systems large aligned speech-to-text corpora are needed. Once aligned, identification of phonemes could be based on samples that are picked-up inbetween phonemes' boundaries. Because manual segmentation is costly and extremely time consuming, automatic methods of alignment are searched for. In this paper, we propose a simple, yet efficient, method for speech to text recognition based on a machine learning approach, using a Romanian speech corpus. [ABSTRACT FROM AUTHOR]