This study investigates the behavior of a feature extraction neural network model trained on a large amount of single language data (“source language”) on a set of under-resourced target languages. The coverage of the source language acoustic space was changed in two ways: (1) by changing the amount of training data and (2) by altering the level of detail of acoustic units (by changing the trip...

ABSTRACT The study assessed the use of rural radio as agricultural information dissemination tool among farmers in Dekina Local Government Area of Kogi State. The specific objectives were to: describe the socio-economic characteristics of the respondents, identify rural and agricultural programmes normally aired on radio, find out the level of patronage of the programmes, identify the convenien...

This study sought to investigate the effect of the two input types interactionally modified input (IM) and textual input enhancement (TIE), the impact of a commonly used learning styles taxonomy as the Visual, Auditory and Kinesthetic learning styles (VAK) by itself as well as the interactional effect of perceptual learning styles and input types on the causative construction development of EFL...

The present study is an attempt to explore the effect of one of the pragmatic elements of discourse (namely the conceptualizable agent) on overpassivization of English unaccusative verbs. Through employing the questionnaire originally used by Ju, (2000), 206 Iranian intermediate and advanced English majors were asked to choose the more grammatical form (active or passive) in target sentences wi...

We present a novel approach that enables a target speaker (e.g. monolingual Chinese speaker) to speak a new language (e.g. English) based on arbitrary textual input. Our system includes a trained English speaker-independent automatic speech recognition (SI-ASR) engine using TIMIT. Given the target speaker’s speech in a non-target language, we generate Phonetic PosteriorGrams (PPGs) with the SI-...

In this paper an innovative approach is presented for MT, which is based on pattern matching techniques, relies on extensive target language monolingual corpora and employs a series of similarity weights between the source and the target language. Our system is based on the notion of ‘patterns’, which are viewed as ‘models’ of target language strings, whose final form is defined by the corpus.

In human-mediated translation scenarios a human interpreter translates between a source and a target language using either a spoken or a written representation of the source language. In this paper we improve the recognition performance on the speech of the human translator spoken in the target language by taking advantage of the source language representations. We use machine translation techn...