TTS Systems for Android

TTS Systems for Android   ABSTRACT There are different kinds of TTS (Text to Speech) systems are already available for Personal computers and web applications. In the Platform of Smart Phone, few of TTS systems are available for Bangla Language. Nowadays android is a popular platform considering Smartphone. There are few Bangla TTS Systems are Available with different kind of Mechanisms and techniques, various kind of tools were used. Here we tried to introduce all mechanisms together and proving a summary above all existing system. Introduction There are more than 250 million people over 4 states of 2 countries in the world speaks Bengali. We are looking for a device which would be able to read any bangla text aloud. So now there is no other device than mobile phone as a better option. There are more than 14 million mobile users in Bangladesh and 30% of them are using smart phones. Use of smart phones are increasing day by day because of reliability, maximum features, capable of using faster internet and eligible for open source application based system. So these kind of features are making our communication very easier and maximum communication is happening over text messaging. So for making our life very easier there are many TTS engines are available for English and many other languages. For bangla there are few more TTS Systems are available in smart phones Platform. Text and Speech both are very powerful communication infliction. If we can make it easier by converting from text to speech or vice versa than it would be a great achievement in communication life cycle, it will make communication easier than before. People would be able to speak their own words by texting only via Mobile Phone. Speech is the most natural form of communication and interaction. Speech Synthesis is a major part of TTS engine and for Bangla it is done in many different ways by different authors. From all those we will get the basic idea of Speech Synthesis Techniques. It is apparent that we are using pre recorded voices for TTS engines yet. Maximum system renders symbolic linguistic representation. So we will discuss about the existing system and possibilities of making the voice very much realistic. The concatenation of final token of speech should be patterned as like real communication. Recorded voices are stored in Database. System differ in the size of the stored units. As for being the speeches or words recorded by human then the clarity may vary. Maximum author tried to put most of the effort to code optimization and database compression. Theyve tried to found many new methods of Speech Synthesis also. Android is a popular Smart phone operating system because of it allows open source applications to install and use, For this reason anyone can try for making better applications for using or business purpose. So it is very important to build a bangla TTS for android. The purpose of our research is to introduce with all of the best TTS Existing systems for Bangla in Android Platform, and ensuring the quality research outputs , findings and Placing possible future works .We discussed about the key points of individual authors and at the end we shown the comparison between all of those. Edification and research for Bangla TTS Engine was improved very highly in last few years. For Android mobile there are many publications available. So here we will discuss about few of them. Case Study 1: After studying the paper Title (A benglai Speech Synthesizer on Android OS), authors names (Sankar Mukherjee and Shyamal Kumar Das Mandal ), we have found that they were trying to develop Bengali speech synthesizer on mobile device. They have used Epoch Synchronous Non Overlap Add (ESNOLA) based concatenative speech synthesis technique for Speech generation. They work hard for database compression because where as space was very limited, small diaphone database was being used in previous days which reduced the quality of synthesized Speech. But in other hand (Pucher, M. and Frohlich, 2005) introduced with large unit selection database, they used a Server for synthesized output speech. It was mandatory to transferred the wave form to a mobile device over a network. They tried a quality output in almost real-time on Mobile device. Speech synthesis is the method of input text data to speech waveforms conversion. The Synthesis method ascertained by the vocabulary size. For utterances of the speech need to be modeled. There are many speech synthesis techniques such as rule-based, articulatory modeling and concatenative technique. But here they developed their synthesizer based on Epoch Synchronous Non Overlap Add (ESNOLA) concatenative speech synthesis method. ESNOLA provides moderate processing for proper matching between different segments during concatenation and it supports unlimited vocabulary without decreasing the quality. So this could be proposed as a good technique of Speech Synthesis. They have designed their full operational method as the given diagram. They divided the system in 4 parts including Input text and output speech state. In between they have planned two important states which is Text analysis module and Synthesizer Module. Where the major operations designed to be performed. A perfect speech required many things such as intonation, prosody, phonological words. And specially handling exception is mandatory while converting text to speech. In this paper they have tried to work with all those parts have mentioned. In their system model they introduced a module named Text analysis module. Which have two sections named phonological analysis module and other one is Analysis of the text for prosody and intonation. They work with the exceptional words at the first Phonological rule part. They developed and implemented phonological rule analysis of the text for prosody and intonation as (Basu, J et al., 2009). They have also work with the exceptional dictionary due to requirement of language analysis. So total processing of text related part ends in phonological analysis module. And synthesizing will be done by the next module. Synthesizer module works for generating a realistic and quality speech .after getting the finalized text from text analysis module they generate a token and then combine splices of pre-recorded Speech and generate the synthesized voice output using ESNOLA approach as in Shyamal Kr Das Mandal, et al. (2007). In ESNOLA approach, the synthesized output speech is generated by concatenating the basic signal segments from the signal dictionary at epoch positions. They synthesized like e.g à  Ã‚ ¦Ã‚ ­Ãƒ  Ã‚ ¦Ã‚ ¾Ãƒ  Ã‚ ¦Ã‚ ²Ãƒ  Ã‚ §Ã¢â‚¬ ¹ = bh + bha + a + aL+o . They had implemented their application in below System specification. Memory management is a major issue in android platform otherwise it wouldnt be used broadly. In this paper they have mentioned that This context will live as long as this application is alive and does not depend on the activities life cycle. It is obtained by calling Activity.getApplication(). They kept the partneme database in external storage card. And the best part is after producing output the final speech file will be deleted. For this TTS system there are total 596 sound files stored in the partneme database. Total size of the database is 1.0 Mb and application size is 2.26 Mb. The best part of this TTS system is it can read Bengali message from phones inbox and it also can generate speech by writing the Bengali word using English alphabet format. Performance And Quality Evaluation is the major part of any Application. Here the total processing time is counting from the starting time ( button is pressed to speak) to the first speech sound is pronounced. They had test the application in many ways and the output of all result is given below They have also judged their application by audience. To measure the output speech quality 5 subjects, 3 male (L1, L2, L3) and 2 female (L4, L5), are selected and their age ranging from 24 to 50. 10 original (as uttered by speaker) and modified (as uttered with android version) sentences are randomly presented for listening and their judgment in 5 point score (1=less natural 5=most natural). The result is given below. The total average score for the original sentences is 4.72 and the modified sentence is 2.88. In their paper, they describe about implementation of a Bengali speech synthesizer on a mobile device. Their goal was to develop a text-to-speech (TTS) application that can produce real time Speech. They modified several components in ESNOLA to make it run on android device. Case Study 2: The objective of a TTS engine is to convert some language Text into its spoken equivalent by a series of modules. For a better TTS engine language modeling and Speech synthesis is major units. After Studying the paper Title( Text to speech for Bangla Language using Festival) authors names (Firoj Alam , Promila Kanti Nath and Dr. Mumit Khan) we found they have used the open-source third party tool Festival TTS engine. Festival provides a frame work for building speech synthesis systems for any TTS engine. The Festival system is written in C++ and uses the Edinburgh Speech Tools Library for low level architecture and has a Scheme (SIOD) based command interpreter for control. Festival Provides API documentation. In their TTS engine they have used two different kind of concatenative methods: unit selection and multisyn unit selection which supported in Festival. In their research they have discussed about Text Analysis, Phonetic analysis Grapheme to phoneme Conversion, Prosodic Analysis, Speech Database or Waveform Synthesis, Speech Output and Analysis of output result. The input text may come in non standard way, considering this problem they have used the text analysis part to convert all non standard words to standard words. Their grapheme-to-phoneme module produces strings of phonemic symbols based on information in the written text. Final speech synthesis is accomplished by concatenative unit selection technique and multisyn unit selection technique. In their proposed system the first step is text analysis. the job of a TTS engine is to convert the input text to equivalent Speech, for this reason the input text should convert to a standard format. There is always a chance that the input text may contain NSW (Non-Standard Word) type words. Here the author listed the NSW words as e.g. numbers (year, time, ordinal, cardinal, floating point), abbreviations, acronyms, currency, dates, URLs. They have used Text normalization for formatting NSW to SW (Standard Word) and they disambiguate the ambiguous token using rule. In their research they didnt work with Unicode directly because Festival doesnt support Unicode, So that they convert Unicode text to ASCII. In text analysis part they Split the token based on white-space and punctuation. They consider white space as a separator and Punctuation can separate the raw tokens. Festival Ordered list of tokens, each with features of white-space, and punctuation. For tokenization White-space is the most commonly used .they have identified Bangla Language have more than 10 types of NSW, so each NSW can identify as separate token by token identifier rules. They used scheme regular expression in festival to identify the token. After identifying of all NSW they convert it to standard word by pronunciation lexicon or (letter to sound) LTS rule. Pronunciation of a word sometimes doesnt match with the pronunciation form. They have solved this problem by using list of lexicon and LTS rule. They inserted 900 lexicons with its pronunciation in the lexicon dictionary. The Steps of Phonetic Analysis within festival: 1. Building large amount of lexicon. 2. Building letter-to-sound rules. They have used three techniques for concatenative synthesis: diphone, unit selection and multisyn-unit selection.They identified 45 phones excluding 31 diphthongs with their features based on articulatory analysis. To build diphone database they include diphthong as well. In their implementation they excluded the diphthongs. The duration they added is taken from Kiswahili TTS system but This is not exact duration for the phone set of Bangla language. They have approximately recorded 500-900 utterance to cover most frequent words of language. The analogy of the system was tested in two ways: in terms of acceptability/naturalness and in terms of intelligibility. Synthesized speech was evaluated on three levels: sentence level, word level and phrase level. In case of sentences level the intelligibility rate being close to 85%. On phrase level it is 83.33% and word level it is 56.66%. In their second experiment, degree of naturalness of the synthesized speech was assessed, again on sentence 90%, phrase 85% and word level 65%. The results Obtained are shown in below Figure. Case Study 3: Their model consist of three part, 1st one is LINGUISTIC MODULE what generate a linguistic representation from text. 2nd one is ACOUSTIC MODULE which generates speech from the linguistic representation. And the 3rd and final one is VISUAL MODULE which driving a talking head based on the linguistic representation. They created a relational lexical database from three source lexica: The Carnegie Mellon Pronouncing Dictionary, Moby Pronunciation II and COMLEX English pronouncing lexicon. There have almost entered 200,000 word, of which over 1500 are non-homophonous homographs. The interesting part of their project is they used animated image which will moved on the subject. In their Linguistic Module they token textual input and looks up word pronunciations and tags in the lexical database. Which words are not present in their lexical database they used a dynamic programming alignment algorithm that algorithm described for aligning sequences from the same alphabets. In Letter-to-sound neural network they defined features for a letter to be the union of the features of the phones that that letter might represent. When they get competitive results they thought that improved performance will come from simplifying the phonological representations found in the dictionary. By this they built a prelimi nary linguistic representation of the utterance. Then the linguistic representation submitted to a postlexical module where lexical pronunciations derived from the lexicon are converted to postlexical pronunciations typical of the speaker. They consider the distance to word, phrase, clause, and sentence boundaries was included. After converting the linguistic representation they send it to the Acoustic Module, which has three stage 1.Duration Neural Network , 2.Phonetic Neural Network and 3.Waveform Synthesizer . The acoustic module established the timing of the speech signal by associating segment duration with each phone in the linguistic representation. An acoustic representation, consist of input parameters for the synthesis portion of a vocoder, is generated for each ten-millisecond frame of speech. Finally, the synthesis portion of the vocoder is used to generate speech from these acoustic descriptions. The most interesting part of their module is that they are providing the video for the speech, so it looks like natural. And that reason they collect the animated image from the nature. The video subsystem takes the output of the linguistic module and the output of the duration neural network and generates an animated figure by using an additional neural network. Case Study 4 : Sanghamitra Mohanty has developed a very intelligent tool, which provides four Indian language Speech output at a time Hindi, Odiya, Bengali and Telegu. For all language she has considered a common system what she named Priyambada. She found Indian languages are phonetic in nature, and the progenitor phoneme mapping is linear. So the vowel and the consonant of the language are almost same except some of them. She took those in consider and apply algorithm for that. We found three stage on this TTS system. First one is Speech Corpora Creation. Here she identified speakers for four native languages, and get them in a laboratory environment using noise cancellation microphone. The sampling rate is 16 bit in single channel of 16000 Hz.By this way she collect the voice from the speakers. Secondly she creates a database for the Different Syllables from the text. She also stored individual polysyllables for different languages in a .wav file format. Finally she played the .wav files for the represented data. There she does not give the solution for the new word what is not in her present. With C++ language she developed a very interesting tool what plays very important role. Case Study 5: They actually focus to normalize the text. Most probably their work is same, their processes are tokenization, token classification, token sense disambiguation and word representation. They found some ambiguous tokens in bangla language. Like, Bangla use many language(English, Arabic, Hindi etc) in their language. the most challenging part of token are the numbers, dates, year, time, multi-text genre etc. To solve this problem they found two ways. One is to token normal bangla language and another table is to handle the ambiguous words. They levels three stage to token a word i) Tokenizer what will used to token the English and other South Asian scripts Bangla ii) Splitter is used for Punctuation and delimiter and iii) to token phone number, year, time and floating point is used Classifier. It also check the contextual rules, different form of delimiters was removed in this stage, for each type of token, regular expression were written in .jflex format all are checked in this stage. To make the ambiguous token natural this part is used for. The ambiguous words like non-natural number cardinal, ordinal, acronym, and abbreviations will sound natural. For this the used some stages. Those are (i). traverse from right to left. (ii). Map first two digits with lexicon to get the expanded form (i.e. 10 à ¢Ã¢â‚¬  Ã¢â‚¬â„¢ ten). (iii). After the expanded form of the third digit insert the token hundred. (iv). Get expanded form of each pair of digit after third digit from the lexicon. (v). Insert the token thousand after the expanded form fourth and fifth digit and lakh after expanded form of sixth and seventh digit. They will continue those stages. After each of second block they insert the token koti to make it natural By this way they believe they can make perfection of 99% of the ambiguous words. Summary of 4 case studies: Topics Case study 1 Case study 2 Case study 3 Case study 4 Case study 5 Tools ESNOLA FESTIVAL NA Priyambada JFlex Processing text type ENGLISH ASCII, UNICODE ENGLISH NOT DEFINED ENGLISH Input text type BANGLA ENGLISH ENGLISH ENGLISH ENGLISH Voice source Pre recorded Pre recorded Pre recorded Pre recorded Pre recorded Total Modules 2 3 Audio format Not define Not define Not define .Wav Not define intonation Yes Yes Yes Yes Yes Utterance Yes Yes Yes Yes Yes Prosody Yes Yes Yes Yes Yes Phonological words Yes Yes Not defined Not defined Yes Exception Handling Yes Yes No No Yes Database length 596 files Not defined 200,000 Not defined Not defined Database size 1.0 Mb Not defined Not defined Not defined Not defined Speech quality evaluation 2.88 out of 5.00 Intelligibility rate No 85% No No Yes Word Processing speed 0.45 sec/ 2 word ( no of syllable -6 ) Not defined Not defined Not defined Not defined Accuracy 57.8% 85% 87% Not define 99% for Ambiguous word [1] Frances Alias, Xavier Servillano, Joan Claudi socoro and Xavier Gonzalvo Towards High-Quality Next Generation Text-to-Speech Synthesis:A multi domain Approach by Automatic Domain Classification,IEEE Transactions on AUDIO,SPEECH AND LANGUAG PROCESSING, VOL16,NO,7 september 2008. [2] Qing Guo, Jie Zhang, Nobuyuki Katae, Hao Yu , High -Quality Prosody Generation in Mandrain Text-to-Speech system, FujiTSu Sci.Tech,J., vol.46, No.1,pp.40-46 ,2010. [3] Gopalakrishna anumanchipalli,Rahul Chitturi, Sachin Joshi, Rohit Kumar, Satinder Pal Singh,R.n.v Sitaram,D.P.Kishore, Development of Indian Language Speech Databases for Large Vocabulary Speech Recognition System, [4] A.Black, H.Zen and K.Tokuda Statistical parametric speech synthesis, in proc.ICASSP, Honolulu, HI 2007, vol IV, PP 1229-1232. [5] G.Bailly, N.Campbell and b.Mobius, ISCA special session: Hot topics in speech synthesis, in proc.Eurospeech,Genea, Switzerland, 2003, pp 37-40. [6] M.Ostendorf and I.Bulyko, The impact of speech recognition on speech synthesis, in proc, IEEE Workshop Speech Synthesis, Santa Monica,2002,pp. 99-106. [7] Text To Speech Synthesis a knol by Jaibatrik Dutta . [8] Silvio Ferreia,Celina Thillou, Bernaud Gosselin, From Picture to Speech: an Innovative Application for Embedded Environment, [9] M.Nageshwara Rao, Samuel Thomas, T.Nagarajan and Hema A.Muthy, Text-to-Speech Syntheis using syllable line units [10] Jindrich Matousek, Josef Psutks, Jiri Krita, Design of speech Corpus for Text-to-Speech Synthesis. Beckman M. and Elam G. Guidelines for ToBI Labeling. Manuscript, version 3, 1997. [11] Corrigan G., Massey N., and Karaali O. Generating Segment Durations in a Text-to-Speech System: A Hybrid Rule-Based/Neural Network Approach. Proc. Eurospeech 97, Rhodes, September 1997. [12] Gerson I., Karaali O., Corrigan G., and Massey N. Neural Network Speech Synthesis. Speech Science and Technology (SST-96), Australia, 1996. [13] Karaali O., Corrigan G., and Gerson I. Speech Synthesis with Neural Networks. Invited paper, World Congress on Neural Networks (WCNN-96), San Diego, September 1996. [14] Karaali O., Corrigan G., Gerson I., and Massey N. Text-to- Speech Conversion with Neural Networks: A Recurrent TDNN Approach. Proc. Eurospeech 97, September 1997. [15] Kiparsky P. Lexical phonology and morphology. Linguistics in the morning calm, ed. by I.S. Yang. Seoul: Hanshin, 1982. [16] Kruskal J. An overview of sequence comparison. Time Warps, String Edits, and Macromolecules, edited by Joseph Kruskal and David Sankoff. Reading, MA: Addison- Wesley, 1983. [17] Linguistic Data Consortium. COMLEX English pronouncing lexicon. Trustees of the University of Pennsylvania, version 0.2, 1995. [18] Miller C., Karaali O., and Massey N. Variation and Synthetic Speech. NWAVE 26, Quebec, October 1997. [19] Nusbaum H., Francis A., and Luks T. Comparative valuation of the quality of synthetic speech produced at Motorola. Research report, Spoken Language Research Laboratory, University of Chicago, 1995. [20] OShaughnessy, D. Modeling fundamental frequency, and its relationship to syntax, semantics, and phonetics. Ph.D. thesis, M.I.T., 1976. [21] Sejnowski T. and Rosenberg C. NETtalk: a parallel network that learns to pronounce English text. Complex Systems 1.145-168, 1987. [22] Seneff S. and Zue V. Transcription and alignment of the TIMIT database. M.I.T., 1988. [23] Tuerk C. and Robinson T. Speech Synthesis using Artificial Neural Networks Trained on Cepstral Coefficients. Proc. Eurospeech 93, Berlin, September 1993. [24] Ward G. Moby Pronunciator II, 1996. [25] Weide R. The Carnegie Mellon Pronouncing Dictionary. cmudict.0.4, 1995.

Comparing My Name is Asher Lev, Naked Lunch and Animal Farm Essay

Comparative Analysis of My Name is Asher Lev, Naked Lunch and Animal Farm  Ã‚        Ã‚  Ã‚   What do a junkie, Communists pigs, and a little Jewish boy have in common? No, this isnÕt an Anti-Semitic crack. In fact, the answer is really nothing. Then how would Naked Lunch, Animal Farm, and My Name is Asher Lev make a good comparative research paper? ThereÕs no magic involved really. To solve this perplexity one must think like Chaim Potok who said that "no feeling, no thought, and no sensibility cannot be tapped or explored and revealed" (Abramson 59). By looking deeper into the fibers of history, satire, criticism, and philosophy that are woven into each of these stories, the connection becomes less ambiguous.    As with many great novels, there is usually more to the story than what is written on paper. Each author, in his novels, incorporated his critical view of the world into the story by using the theme of individual vs. society. These views portray their cultures in the negative light in which they saw them. Therefore, the criticisms were the authorsÕ way of exhibiting and lashing out against what, in their minds, were the evils within the society they lived in. These problems range from politics, to religion, to the human condition.    My Name is Asher Lev, Naked Lunch, and Animal Farm were all written with a specific, social criticism in mind. Chaim Potok, author of My Name is Asher Lev, though an ordained rabbi of the Jewish faith, (Abramson 2) sought to justify the "conviction that no idea should be foreign in our world (Potok)" by challenging the JewÕs belief that "art holds no place in the Jewish faith. (Kremer)" Though raised in a strict, Orthodox household Potok grew interested in art from an early age and,... ...l. 2. Feb, 1976. 321-322. Potok, Chaim. Interview with Jennifer Gilmett. Seattle Pacific University. 29 Oct. 1997.http://www.lasierra.edu/~ballen/potok/Potok.interviews. SPU.html Potok, Chaim. Lecture. Southern College of Seventh-Day Adventists. Collegedale, Tenn. Ed. Dr. Jerry Gladson. http://www.lasierra.edu/ ~ballen/potok/Potok.unique.html#Asher Seltzer, Alvin J. Contemporary Literary Criticism. Vol. 42. Detroit: Gale Research Company, 1985. 80-85. Skerl, Jenny. "William S. Burroughs". http://www.bigtable.com/0009e.html Smyer, Richard I. Animal Farm: Pastoralism and Politics. Boston: TwayneÕs Masterwork Studies, 1988. 11-30. Smyer, Richard I. "Primal Dream and Primal Crime: OrwellÕs Development As a Physchological Novelist". DIScovering Authors Modules Online. University of Missouri Press, 1979. http://www.galenet.com         

The Prevalent Issues Of Surrogate Parenting :: essays research papers fc

The Prevalent Issues of Surrogate Parenting   Ã‚  Ã‚  Ã‚  Ã‚  Surrogate parenting refers to an arrangement between a married couple who is unable to have a child because of the wife's infertility and a fertile woman who agrees to conceive the husband's child through artificial insemination, carry it to term, then surrender all parental rights in the child. Often, the surrogate mother receives compensation for her services. The final step in the process is typically the father's acknowledgment of paternity and adoption, with his wife, of the child. Through surrogate motherhood, a couple desiring a child need not wait an indefinite number of years for an adoptable baby, as generally happens at the present time. The married couple obtains a child who is the husband's biological offspring- a child for whose existence both husband and wife can feel responsible.   Ã‚  Ã‚  Ã‚  Ã‚  Surrogate parenting is highly controversial by its very nature. Nevertheless, surrogate parenting is attracting wide spread attention as a viable alternative for infertile couples intent on having a child. Contract surrogacy is officially little more than ten years old, although surrogate mothering is a practice that has been known since biblical times. In 1986 alone 500 babies had been born to mothers who gave them up to sperm donor fathers for a fee, and the practice is growing rapidly.   Ã‚  Ã‚  Ã‚  Ã‚  For this reason there are many questions and doubts that arise from this subject. Often there are many legal difficulties that come about with surrogate parenting. In some states the contracts that insure the infertile couple the baby of the surrogate mother mean nothing. This, in turn, can cause huge problems if the surrogate mother were to change her mind about giving up her child. Who has the rights to the child in this awful situation? Surrogate parenting is a wonderful alternative for infertile couples as long as all party's involved are educated on the subject and are fully aware of the pros and cons of this risky business transaction.   Ã‚  Ã‚  Ã‚  Ã‚  Unfortunately laws on surrogate parenting aren't very helpful. Increasing numbers of surrogate custody cases are finding their way into the courtrooms. The most dramatic problem arises when the surrogate mother decides she wants to keep the baby.Whether she decides early or late in the pregnancy, at birth, or after the child is born, the ultimate issue is whether she or the infertile couple have parental rights.   Ã‚  Ã‚  Ã‚  Ã‚  How is the law to respond to this kind of problem? Normally people would agree that a contract is a contract and therefore the infertile couple should be the ones to receive the baby. Unfortunately for some of us more sympathetic people this decision is not that simple.

The Euro :: essays papers

The Euro In 1991 it was decided that the Euro would be introduced. It officially became the currency of eleven European nations: Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Portugal, and Spain, shortly thereafter. Although the actually hard currency will not be introduced until January 1, 2002, it is possible to trade and complete transactions using this currency. This introduction allowed for a single money supply throughout most of Europe, caused increased transparency of prices and stocks throughout the nations adopting it and encouraged long-term investments between firms in different countries by eliminating exchange rate risk. Despite these benefits, the launch of the Euro has not gone as successfully as planned. Since it’s introduction the Euro has lost almost one third of it’s value compared to the dollar. This devaluation has the potential to create a large negative effect on European markets. To take control of the situation government intervention was deemed necessary. In early September, the European Central Bank lowered interest rates for the sixth time in less than a year, in hopes of initiating a rise in the value of the Euro. Despite these efforts the value of the Euro continued to falter. Then in late September central banks from many powerful economic nations collaborated in a major invention effort. The banks spent billions buying Euros to increase their demand while simultaneously selling dollars and yen. This effort seemed to have work as the Euro finally stabilized. This invention was an important step because a weak Euro would cause investors to lose confidence in the new currency. In addition it created a risk of increased inflation because of the increased expense of imports. However, the Euro is still not out of danger because many analysts feel that the reason that it is performing so poorly is because of the decreased amounts of investments in Europe as other markets, the United States in particular, continued to flourish. This is a long-term problem that the central banks will be unable to fix. Then in November as there were signs of slowing economic growth in the US the value of the Euro started to increase. By late November many businesses were acquiring a preference for the Euro because of the benefits it provided. According to one article, â€Å"The Euro has revolutionized corporate strategy and transformed approaches to doing business in Europe.

Eating Disorders Essay -- essays research papers fc

An eating disorder is an illness that involves an unhealthy feeling about the food we eat. â€Å"Eating disorders affect 5-10 millions Americans and 70 million individuals worldwide† (www.eatingdisorderinfo.org 1). They also affect many people from women, men, children, from all ages and different races. People who have eating disorders usually see themselves as being fat when they really aren’t. This usually deals with women or teenage girls mostly. They watch television, movies, read articles in magazines, and see pictures of the celebrities whom they want to be like because they have the â€Å"ideal body† that everyone wants and craves for. The media makes us all think we need those types of bodies to be happy with ourselves, be more successful in life, and be perfect. Starving yourself or eating less amounts of food doesn’t help you get the â€Å"ideal body† that you desire to have. This shows that you lack self-esteem and only want to see what other people see in life. This may impinge on people who are alone and want to get attention and by doing this they want to be thin. There are many different kinds of eating disorders that people are affected with. For example, there is Anorexia Nervosa, which deals with not eating regularly or eats little amounts of food or not eating at all. There is also Bulimia Nervosa, which is when a person eats a large amount of food and then binges or purges after to get rid of the food they just put into the body. Lastly there is the Binge eating disorder. This disorder is when a person keeps a secret from everyone of their excessive eating. â€Å"Women make up more than 90 percent of people with these eating disorders† (www.4woman.gov 1).â€Å"However, young women are most vulnerable, particularly between the ages 15-25 years† (www.edauk.com 1). Women are more likely to be anorexic, because they always see other women with thin bodies and feel pressured to want to be like them. They may be alone or divorced and may need attention so they look for ways to get that attention from people. â€Å"The women suffer with feelings of self-hate, worthlessness, low self-esteem, and they usually feel that in order to be happy, they must be thin† (www.mirror-mirror.org 1). Women in the business industry feel they don’t get enough attention from people so in order to heighten their career, they put themselves out there to have the perfect body to get people’s att... ... illness. If you do not seek help you can damage your body, cause major health problems, and even death. But if you do seek help, you can increasingly build up your self-esteem that helps cope with the illness. Bibliography #1 - Thompson, Colleen. Eating Disorders. Internet Explorer December 9, 2002 #2 - Thompson, Colleen. Children. Internet Explorer December 9, 2002 #3 - Thompson, Colleen. Women. Internet Explorer December 9, 2002 #4 - Thompson, Colleen. Binge Eating Disorder. Internet Explorer December 9, 2002 #5 - Thompson, Colleen. Anorexia Nervosa. Internet Explorer December 9, 2002 #6 - Thompson, Colleen. Bulimia Nervosa. Internet Explorer December 9, 2002 #7 - Hendrick, Victoria Eating Disorders. Internet Explorer July 2002 #8 - Spearing, Melissa. Eating Disorders. Internet Explorer. August 6, 2002 #9 – Anonymous. EDA. What is an Eating Disorder? Internet Explorer. March 31, 2004 #10 – Anonymous. Eating Disorders Statistics. Internet Explorer. http://www.eatingdisorderinfo.org #11 - Harmon, Dan. Anorexia Nervosa Starving for Attention. Philadelphia: Chelsea House Publishers 1999 #12 - Nardo, Dan. Eating Disorders. San Diego, California: Lucent Books, Inc. 1991

Discuss how Hare presents ideas about class in this scene and at least one other point in the play

Within Hare’s play Murmuring Judges, there almost appears to be two class systems. The first is the standard upper, middle and lower, however, Hare almost separates the prisoners, the police and the lawyers as three separate classes of people, who each look down on the class below them. This allows us to see not only the perceived separations of social classes but also the classes that you are put into according to you profession and the classist attitudes held by those above. In the focus scene, Hare clearly shows his views about class through implications and connotations used in the lawyers and judges conversations. Immediately as the scene starts, â€Å"His Excellency AL Hadji Sulay Ibrahim Dunko† is announced by the toast master. Whereas within the perceived lower class of the police, DC Abdul Khan is referred to as Jimmy, here he is announced with his full name and title, which immediately suggests a difference in class and status between the two men. This is also clearly shown in the language used by all the characters in this scene, as phrases such as â€Å"Grand Days† and â€Å"the fishy stuff† in reference to caviar creates a semantic field which suggests the men view themselves and believe they are viewed by others as upper class. Furthermore, the juxtaposition of the Toast Master and Gerard at the opening of Act 2 clearly demonstrates the social classes, as we see the announcement of important men next to a man monologuing within his prison cell. Hare uses food in the focus scene to reflect the upper class nature of the men. As previously referenced, Cuddeford calls caviar â€Å"the fishy stuff†, suggesting his familiarity with highly expensive foods, which subtly exposes his class. Again, the â€Å"Roast Venison Baden-Baden† also shows the dinner to be sophisticated and the suggestion that â€Å"[the students] have to eat their way through twenty four dinners† reveals the recklessness of the system in terms of man, which clearly suggests there is money to be thrown around. Hare also uses food in other moments in the play reflect the lower classes of the police and the prisoners. Whereas Gerard is only once offered a cup of tea, Woody’s line â€Å"your glass of beer? † shows Woody to act â€Å"like a manservant† which again clearly shows the difference between the two men. However, it could be argued that Sir Peter sees himself as more important than he really is, as he sends Woody to ask Irina to the opera in order to make himself seem too important to come in person, which isn’t reflected anywhere else in the play. Similarly, Hare uses other running motifs throughout the play which suggest the upper class nature of the lawyers, but also to suggest the lawyer’s ideas about the lower classes. The discussion of Desert Island Disks clearly shows them to be at least middle class, as do Sir Peter’s selections, but the comment â€Å"everyone listens to desert island disks† is what exemplifies how out of touch with reality the lawyers are. This unrealistic idea of society is also shown by Sir Peter, â€Å"I thought all educated young women loved music†, as this is rather an idea of the past then the present. Hare uses reading to show the inherent difference between the lawyers and the prisoners especially, as he presents the lawyers as having â€Å"no time to read off the job†, whereas Gerard sarcastically states â€Å"Thank God for literature† as whilst the lawyers claim to have no time, the cruel irony is that all Gerard has is ‘time’. The lawyers views on those they perceive to be lower than them is never hidden, possibly as the lawyers are largely untouchable due to their position, as shown by the conversation with the Home Secretary, which shows the lawyers to have acquaintances in the government. Cuddeford openly calls the suspects â€Å"common-as-much individuals† which shows the upper classes to think themselves much better than everyone else. This is further shown by â€Å"[the prisons] may be called failings of society†¦ which are truly not my concern† show disinterest in the justice of those beneath them, again shown by Sir Peter’s unwillingness to do criminal law as â€Å"it involves real people†. On a larger scale, Sir Peter shows not only the suspects but the whole idea of crime to be â€Å"trivial†, as he refers to Gerard’s case, which clearly upturns Gerard’s life, as â€Å"a silly sort of warehouse robbery†. Sir Peter further expresses his view on Gerard later, claiming he is â€Å"an ordinary, sub-average human being†, demonstrating the barriers he believes exist between them. Gerard is also presented as aware of these separations, as shown through â€Å"these men†¦ will go home to wine in fine glasses and the gossip of the bar†¦and I will go to my gaol†. Gerard’s reference to himself as â€Å"the stuff of their profession† suggests that Gerard perhaps also sees himself as below the lawyers, which could be used to argue that class separations are inherent. This inference is reinforced by â€Å"there is a glass screen and our clients live on the other side of it†, which not only suggests a separation but also could be seen as excusing the seemed inability of the legal system to help its clients. Although largely presented as incapable or unwilling to help their clients, the lawyers are clearly shown to cover their own backs. At the time, there was a suggestion of changing laws regarding barristers which would, according to Sir Peter, would be â€Å"a threat to justice†. In response to this, Irina, under instruction, starts a campaign against the new legislation which raises ?1million in four days. This is heavily ironic within the play, as it is often states there is no money to reform the prison, which given the events of the Strangeways riot in April 1990, would presumably be a higher priority. It also shows the extent to which the lawyers are upper class, as the blase attitude of â€Å"give or take a few thousand† shows how small an amount of money this is to them, which would be huge to any other characters in the play. Cuddeford is shown to be clearly aware of this, â€Å"play down the million†, which suggests a level of guilt at using the money for this, especially within their profession. In conclusion, Hare uses juxtaposition throughout Murmuring Judges to show the seemingly inherent differences in class between the lawyers and the prisoners in particular. Whilst the prisoners are forced to â€Å"slop out† and â€Å"throw shit packages†, the lawyers are often presented in luxurious settings, â€Å"laid out magnificently four different wine glasses†. Hare also presents ideas of class mainly from the perspective of the lawyers who seem themselves as more important than they perhaps are, and certainly better than the â€Å"common-as-muck† ordinaries. Overall, I think the ideas of class in the play are nicely represented in the line â€Å"we were going to abolish this as outdated†, but in the end didn’t, which for me shows the lawyers understanding that the system is incapable or unwilling to work to the best of its ability, but simply would rather not out of tradition.

Bourdieu and social class within the educational system

The subject of social class within the educational system seems to be the elephant in the room. Issues of race, gender, discrimination and making safe places are addressed constantly within the pedagogy yet we ignore the realities of social stratification, especially when it comes to the classroom and the curriculum we are expected to teach. According to Bourdieu, the education systems of western societies function in such a way as to legitimatize class inequalities (Bourdieu, 1977).Success in the education system is enhanced by the possession of cultural capital (which is etermined the dominate culture) and Lower-class pupils do not, in general, possess these traits. Bourdieu then supposes that the failure of the majority of these pupils is inevitable. This, he postulates, explains class inequalities in educational attainment. , For Bourdieu, educational credentials help to reproduce and legitimatize social inequalities, as higher-class individuals are seen to deserve their place in the social structure.Place in the social structure is not pre determined and education often is a factor in the upward mobility in SES. Muller and his team describe cross-national imilarities and differences in the two steps in which education intervenes in the process of intergenerational class mobility: the link between class of origin and educational credentials attained, and between these credentials and class position allocated to (Muller et al. , 1989).They conclude that the patterns of association between class origin and education, and between education and class destinations are similar across the nine nations. However, the strength of these associations demonstrates cross-national variations. This paper is one of the first comparative tudies of social mobility, which used the data sets collected in the early 1970s from nine European countries investigated in Comparative Analysis of Social Mobility in Industrial Nations (CASMIN) project.Nevertheless, this article supports FJG hypothesis which argues that class origin inequalities in relative mobility chances will be roughly constant across nations . Social mobility, class and education is further explored through a longitudinal study conducted by Johnson, Brett & Deary (2009). They proposed that social class of origin acts as ballast, restraining otherwise eritocratic social class movement, and that education is the primary means through which social class movement is both restrained and facilitated, thereby giving weight to Bourdieu's theory of Cultural Reproduction.They conclude that parental social class attainment contributes to educational attainment, which in turn contributes to participant social class attainment, suggesting that educational attainment contributed to social class stability. Education is important to social mobility and, thus, appears to play a pivotal role in the association between ability and social class attainment. When looking at the relationship between ability and socia l class attainment, it is useful to also look at the different types of culture capital.Andersen and Hansen (201 1), for example, distinguish between two interpretations of cultural capital: â€Å"narrow' and â€Å"broad. † The narrow interpretation refers a child's exposure to ‘high cultural' products or activities (Bourdieu's concept ot objectified capital): tor example, having objects of art at home, or a tastefully furnished home, visits to the theatre or art museums, or playing the piano (p. 608). These signs of high culture may not mprove a student's work in any objective way, but they are rewarded through subjectivity involved in assessing academic performance.The same is true of the broad interpretation of cultural capital, which is â€Å"general linguistic skills, habits, and knowledge, including cognitive skills,† which are â€Å"used in a strategic manner by individuals, who thereby may receive advantages or profits† (p. 608). This kind of cult ural capital is passed from parents to children through school work (p. 608). Bourdieu's description of educational capital encompasses this outlook. One ofAndersen and Hansen (2011) implications in schools which supports Bourdieu's theory of cultural capital is that: â€Å"Students from classes with highest cultural capital will perform the best academically, on each horizontal level† (of social class) (p 611) This is often seen played out when looking at the Socio Economic Status schools. Bankston and Caldas (2009) examine how legal desegregation of American schools starting in the 1950s and 1960s was countered by de facto segregation due to â€Å"social class, residential patterns† and other forms of social marginalization.Since the verage socioeconomic status of a student population affects a school's educational achievement levels, upper and middle class families eluded and hindered desegregation by moving to different school districts, suburban communities, by ch oosing private schools etc. Bourdieu's concept of education through institutional capital sees education as a place where one acquires the skills to enter different positions within the labour force -and those positions in turn determines one's socioeconomic status..Bankstone and Caldas state that policy assumes that differences in educational achievements are caused by the concrete schools and in articular by its teaching staff. Schools are believed to determine socioeconomic conditions instead of the other way around. As educators, not only must we be aware that class differences are present in the classroom, but, perhaps, look for ways to minimize the gulf between classes and increase capital culture in those who do not possess as much as others. Technology may be one way to do this. There seems to be a push towards using new technologies in the classroom.Considering class inequality and cultural capital, an educational model that aims to bridge the divide by bringing students to gether to the ame level of technological proficiency would be desirable. Kapttzke (2000), following a case-study in an Australian school, concludes that integrating student- based projects using information technology is a way to bring students with tech sa'. n. y back from the brink of alienation. Kapitzke states that â€Å"teachers who ignore the texts, identities, skills and interests of the young do so at their own peril. † (p. 0) Faced with a growing techno-cultural capital gap, educators need to â€Å"view students as fellow explorers and co-workers† (p. 60) and possibly working on innovative rojects like revamping a school's computer network. The student who led the project ended up teaching not only students but teachers too. Not only would cultural capital be affected, it is most likely that a student's social capital Conversely, a study done in Californian schools shows a different side of the story. Cuban (2001) and fellow researchers explored the paradox of high access to technology with low real use.This was explained by traditional constraints on teachers such as time and structure, as well as annoying deficiencies in the technologies, such as computer crashes, that limited teachers' initiatives. The teachers stressed â€Å"that using computers in their classes made demands upon them that made their Job harder. † (p. 828) In the end, â€Å"inadequate time in the daily schedule to plan work together goes to the heart of teacher use of new technologies and their preferred teaching practices† (p. 28) and resulted in the teachers preferring traditional teacher-based discussions, lectures and activities supplemented with some time for technologies. Cuban and his colleagues believe that technology will never revolutionize the classroom; instead, â€Å"historical legacies of high schools in their chool structures and technological flaws will trump the slow revolution in teaching In conclusion, the Kapitzke article highlights an innovative practices† (p. 830). way of maximizing tech-sawy students' cultural capital and thereby pushing for equality and integration.However, as the Cuban article points out, technology will likely be relegated to special projects when deemed appropriate by a teacher relying on various methodologies. While dynamic technologically innovative teaching methods have their place they are not the magic answer to solving cultural capital and class inequalities.