Political speeches are represented in different shapes as political forum, events or as inaugural speech. This research critically analyzes the inaugural Speech of the President Donald Trump which was delivered on 20th ,January, 2017 from the site<www.cnn.com> retrieved on 10th ,May,2017. The objectives of the study are: First: classifying and discussing well known micro structures (linguistic feature) of the speech, and second: classifying the macro structures i.e. the delivered political inaugural speech in which he includes social structures. To reach to the objectives of the study, the researcher will adopt Norman Fairclough’s three dimensional Analytical Model(1989). Tracing the model, the speech was submitted to description (text analysis), interpretation (processing/ analysis) and explanation (social practice and analysis). The results of the analysis have shown that Trump uses colourful language devices to address Americans. He uses future tense in his speech more than the other tenses to talk about America's future. He creatively repeats certain expressions to show his point of view. The pronoun 'we' is used to talk about the state of America and to show a mutual correlation between Trump and the hearers. Moreover, Trump relays on active voice to get all the hearers active not passive, which reflects the social relations. However, in some instances, he uses passive voice to assure Americans that he will be with them
Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the
... Show MoreRecognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),
... Show MoreAbstract
Currently, the “moderate discourse and civil peace” represents a rich and important topic for scholars, due the rise of waves of extremism and Islamophobia campaigns, and what that leads to in term of imbalance in relations between nations and peoples.
Based on that, the research approach was to tackle the culture of hatred and calls for the clash of civilizations.
In order to contribute to solving these problems caused by cultural and religious prejudices, I decided to address the topic of “moderate discourse and civil peace” through two essential axes:
- Features of moderate religious discourse
- The role of moderate discourse in establishing communit
The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
BN Rashid, International Journal of Research in Social Sciences and Humanities, 2019 - Cited by 1
Students' passive listening to their teacher's reading is one of main
reasons behindtheir weakness in the reading skill which in its turn may
hinderachieving the in desired objectives.
When exploiting critical thinking, which will lead to deeper
understanding of the intellectual content, in learning and accurate and
correct students' outcomes.
Active listening allows paying attention to the speaker, asking him,
arguing with him, judging what he says, and making decision on what
he says. For this reason, the researcher felt the need for preforming a
study to identify the effect of critical listening on developing students'
critical thinking at reading in the Kurdish language department.
The researcher has
The process of name calling in the propaganda discourse is one of the most important methods of persuasive propaganda act, based on the ideology of working with the function, and the valuation of this function, creating a hermeneutic representation of the meaning falls within a specific format and responds to a specific function, which is the realization of the intent of the propaganda doer in persuasion and persuasion through negative and positive propaganda logic. The method of name calling has played a dangerous and horrific role in conflicts and ideological and military wars throughout history.
This study aims to find out the mechanisms of semiotics system behind discourse of propaganda far from substantive&n
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