The empirically robust phenomenon of impaired verbal short-term memory due to task-irrelevant background speech is known as the Irrelevant Sound Effect (ISE). Yet, underlying cognitive mechanisms are still not fully resolved, like whether phonology-based interference contributes disruptive effect on serial recall. Thus, we tested ISE for such a speech-specific aspect by varying phonological con...

This paper addresses mismatch between speech processing units used by a speech recognizer and sentences of corpora. A standard speech recognizer divides an input speech into speech processing units based on its power information. On the other hand, training corpora of language models are divided into sentences based on punctuations. There is inevitable mismatch between speech processing units a...

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

abstracttask-based language teaching is considered an effective way to achieve a harmony between grammar and communication. the present study investigates two different ways of teaching modal verbs: task-based versus traditional approaches. to this purpose, an oxford placement test was administered to select 40 homogeneous participants out of a larger population who took this test. the selected...

with regard to the impossibility of preparing learners for each situation that they might encounter in their life, it is more logical to teach them how to cope with unexpected challenges. helping learners ‘learn how to help themselves’ can be facilitated by means of tasks and activities in the classroom context. this paper presents some of the find- ings of a study on iranian young learners bet...

The construction of acoustic models for speech recognition systems is a very costly and time-consuming process, since their robust training requires large amounts of transcribed speech data, which have to be collected and labeled by humans. This paper describes an approach for costeffective construction of task-adapted acoustic models. Existing speech data(bases) are employed to set up a large ...

This paper focuses on the task of tagging text with their parts of speech. The methodology chosen for this task is the Maximum Entropy based Model and although complex will only be explained briefly. More importantly, the focus will center on the differences in performance of the maxent model with varying feature sets compared to the baseline model. One problem highlighted in part-of-speech tag...

The current study presents findings from a mixed-methods study of investigating the self-regulatory role of private speech (self-talk) on students’ translation quality. The aim of the study was to validate the adapted version of a self-verbalization questionnaire. The construct validity and reliability of the scale were supported by the CFA which revealed that all items reached the acceptable f...

End-to-end attention-based models have been shown to be competitive alternatives to conventional DNN-HMM models in the Speech Recognition Systems. In this paper, we extend existing end-to-end attentionbased models that can be applied for Distant Speech Recognition (DSR) task. Specifically, we propose an end-to-end attention-based speech recognizer with multichannel input that performs sequence ...