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Register a new userHumor and irony in the tale on the tongue of animals at Lafontaine and Ahmed Shawki
الفكاهة و السخرية في الحكاية على لسان الحيوان عند لافونتين و أحمد شوقي
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Aِl-Baath University ورقة بحثية
Publication date
2018
fields
Arabic
and research's language is
العربية
Created by
Shamra Editor
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إنّ هدف الشّاعرين لافونتين و شوقي من توظيف السّخرية و الفكاهة في حكاياتهما على لسان الحيوان ، هو إيجاد قيم خلقيّة متّصلة بروح العصر و أحداثه ، و تقديم العظة و العبرة النّاتجة من التّجربة و عمق المعاناة ، و امتاع القارئ و تسليته و التّرويح عن نفسه .
The goal of the poets Lafontaine and Shawki to employ ridicule and humor in their tales on the tongue of animals, is to create moral values related to the spirit of the times and events, and provide the sermon and the lesson resulting from experience and depth of suffering, and enjoy the reader and entertain himself.
References used
Prop, Vladimir, 1996 CE – 1416 AH, the mythology of the story. Translation: Dr. Abdul Karim Hasan, Dr. Samira Ben Amo, I, Sheraa for Studies and Publishing, Damascus
Alhlwi, Hassib, 1956 CE, French literature in his golden age. part 3, edition 2
Hamida, Dr. Abdul Razzaq, 1951CE, Animal Stories in Arabic Literature. The Anglo- Egyptian Library, Cairo
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The research refers to the artistic and stylistic features of the story of the animal Lafontaine's poetry, which is the multiplicity of sources and diversity of stories, spirit of humor, the varied rhythm of music, the story and its relation to social
criticism.
Language is one means of communication that has the most significant role in enhancing
humans' life and their relation with their environment alongside their relations with the
society in which they were born and raised. Language has always been th
e product of this
society on whose progress and regress have an impact upon it. It is well-known that
standard Arabic is the official language with its accurate grammar and vocabulary moving
from the ancestor to the descendant. However, it very often may be difficult to apply or
have access to for most people regardless of their cultural qualifications. It is also difficult
for this language to convey or transfer reality as clear as it is or to express how easy and
spontaneous life is to all people. Since the phenomenon of vernacular language alongside
standard language is a linguistic one all over the world, thus the necessity in the Arabic
novel in general and countryside in particular emerged to have an in-between third
language that is neither standard nor vernacular. This novel language is to be capable of
bringing the standard closer to daily life and ending up with one form of dialogue that
provides characters with their psychological and social traits; a tacit language for all
different cultural and scientific levels of readers and their social status. Also, this language
will help the text express the human emotions that emerge subconsciously for the standard
one is incapable of doing so. Needless to say, standard Arabic was one day a vernacular
with different dialects expressed through words like "language" and "tongue." Allah said:
("We have not sent but a messenger to represent his nation and clarify the truth to them.
For, God guide and misguide whomsoever thus He is the Noble and Wise").
This paper describes our contribution to SemEval-2021 Task 7: Detecting and Rating Humor and Of-fense.This task contains two sub-tasks, sub-task 1and sub-task 2. Among them, sub-task 1 containsthree sub-tasks, sub-task 1a ,sub-task 1b and sub-task 1c
.Sub-task 1a is to predict if the text would beconsidered humorous.Sub-task 1c is described asfollows: if the text is classed as humorous, predictif the humor rating would be considered controver-sial, i.e. the variance of the rating between annota-tors is higher than the median.we combined threepre-trained model with CNN to complete these twoclassification sub-tasks.Sub-task 1b is to judge thedegree of humor.Sub-task 2 aims to predict how of-fensive a text would be with values between 0 and5.We use the idea of regression to deal with thesetwo sub-tasks.We analyze the performance of ourmethod and demonstrate the contribution of eachcomponent of our architecture.We have achievedgood results under the combination of multiple pre-training models and optimization methods.
Humor recognition is a challenging task in natural language processing. This document presents my approaches to detect and rate humor and offense from the given text. This task includes 2 tasks: task 1 which contains 3 subtasks (1a, 1b, and 1c), and
task 2. Subtask 1a and 1c can be regarded as classification problems and take ALBERT as the basic model. Subtask 1b and 2 can be viewed as regression issues and take RoBERTa as the basic model.
Humor detection and rating poses interesting linguistic challenges to NLP; it is highly subjective depending on the perceptions of a joke and the context in which it is used. This paper utilizes and compares transformers models; BERT base and Large,
BERTweet, RoBERTa base and Large, and RoBERTa base irony, for detecting and rating humor and offense. The proposed models, where given a text in cased and uncased type obtained from SemEval-2021 Task7: HaHackathon: Linking Humor and Offense Across Different Age Groups. The highest scored model for the first subtask: Humor Detection, is BERTweet base cased model with 0.9540 F1-score, for the second subtask: Average Humor Rating Score, it is BERT Large cased with the minimum RMSE of 0.5555, for the fourth subtask: Average Offensiveness Rating Score, it is BERTweet base cased model with minimum RMSE of 0.4822.
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