By Maya Singh
The experiment of Self-Help Group (SHG) by Sewa Bharati proved a major success in the remote areas of Jharkhand. Presently, there are over 1400 SHGs in the state run by Sewa Bharati activists. Every group normally has 15-20 women. This number goes over 25,000. Today, these women are writing a new chapter of change after achieving self-respect and self-dependence with the help of SHGs.SHGs have brought about a sea-change and awareness among the women who are mostly illiterate. They not only developed the feeling of taking group decisions but also to get rid themselves of the clutches and atrocities of private moneylenders. They not only changed their own life but also extended a helping hand to the needy persons of the society. Women of a similar group in Ranchi helped in eye operation of a minor child at Shankar Eye Hospital in Chennai. The women in the group of Meera, Rani and Neetu make bari, papar, pickle, spices, jute bags, etc. Arati, Anuradha and Sanyukta impart training of making candles, growing mushroom, making jam and jailly and also sell the goods made by them. Malati and Keshwanti of Tupudana received the training of making bangles by lakh and goods of jute from Jaipur. Now they not only make all these things themselves but also impart training to other women. They organise stalls of the goods made by them under the banner of Sewa Bharati in various fairs and exhibitions. Some sell the products in local markets while some move up to Delhi to participate in the trade fair organised at Pragati Maidan every year.The group of women, led by Malati of Tupudana purchased a tractor with the help of a bank and earned money by running it on hire. When the Block Development Officer (BDO) of Khunti misguided Mateshwari Devi regarding the time of foundation stone laying ceremony of a road at 6.00 am in the morning, she, along with other women, went to the spot at 4.00 am and blocked the road to protest against the mischief of the BDO. Finally, Malati got the contract of making that road and she did the work with dedication and received appreciation from all. The SHG of women led by Arati of Namkom purchased an auto-rickshaw and got contracts of building roads, ponds and government buildings.The women take part in social activities too with full activism. Sarika of Khunti district foiled the game plan of a married person who was going to marry another woman despite having one wife. She earned praise from the people through this conduct. Similarly, Arati, Sanyukta and Anuradha of Namkom jointly got a wedding ceremony stopped, as the groom was addict. They also forced the groom's parents to pay the expenditure of the bride's family on the marriage. They later married that girl with a suitable boy after some time. The women of Bokaro who mostly work as midwives helped their husbands who are mostly rickshaw-pullers and work as collie, to learn at least doing signature. Now they proudly say that nobody in their group is illiterate. They are also very punctual in their activities, which is praised by all.Sumitra Devi and Manodevi of Dhanbad admit that their life has changed considerably after joining the SHGs and Samskar Kendras run by Sewa Bharati. They not only felt the change in their individual life but also got more respect by their husbands and the society. The women of Gumla purchased foodgrains in bulk and sold it after some time, which helped them in earning good profit.A woman of Gumla was not going to her in-laws' house. She had the bad habit of fighting with everybody. She levelled various allegations against her husband and every time she refused to go with him. The women of SHG persuaded her husband and sent her with him. The women of Pakud district organised a mass marriage ceremony and got married 125 pairs.Such change comes silently and leaves lasting impact. All this has been possible only due to the involvement of the Sewa Bharati workers with the projects from hearts.
Tuesday, May 19, 2009
Panini to the rescue for a computational grammarian
Panini to the rescue for a computational grammarian
Research team turns to the “world’s first computational grammarian!”.
http://www.thehindu businessline. com/ew/2009/ 05/18/images/ 2009051850090301 .jpg
K.V. Kurmanath
Panini, the legendary Sanskrit grammarian of 5th century BC, is the world’s first computational grammarian! Panini’s work, Ashtadhyayi (the Eight-Chaptered book), is considered to be the most comprehensive scientific grammar ever written for any language.
According to Prof Rajeev Sangal, Director of IIIT (Hyderabad) and an expert on language computation, Panini’s epic treatise on grammar came to the rescue of language experts in making English unambiguous. English is more difficult (as far as machine translations are concerned) with a high degree of ambiguity.
Some words have different meanings, making the analysis (to facilitate translations) a difficult process. Making it disambiguous is quite a task, where Panini’s principles might be of use.
Ashtadhyayi, the earlier work on descriptive linguistics, consists of 3,959 sutras (or principles). These highly systemised and technical principles, some say, marked the rise of classical Sanskrit.
Sampark, the multi-institute effort launched to produce a translation engine, enabling users to translate tests from English to various languages, will use some of the technical aspects enunciated by Panini. “We looked at alternatives before choosing Panini,” Prof Sangal says.
Incidentally, Prof Sangal co-authored a book, Natural Language Processing – A Panini Perspective, a few years ago.
Besides the technical side, Panini would be of great help to researchers on the translation engine on the language side too.
A good number of words in almost all the Indian languages originate from Sanskrit. “That is great because Indian languages are related to each other,” Prof Sangal points out.
kurmanath@thehindu. co.in
http://www.thehindu businessline. com/ew/2009/ 05/18/stories/ 2009051850090300 .htm
Break the language barrier
Word for word: More on the Sampark initiative to enrich translation. .
Look at the sentence — The Chair chairs the meeting. How will a machine understand this?
http://www.thehindu businessline. com/bline/ ew/2009/05/ 18/images/ 2009051850070301 .jpg
K.V. Kurmanath
Telugus, Kannadigas and Malayalis can read Subrahmanya Bharati, the legendary Tamil poet, and relish the sweetness in his poetry. Similarly, Premchand, Tagore, M T Vasudeva Nair, and U R Ananthamurthy too could be read and understood by readers in other languages.
All this will soon be a reality, thanks to a project initiated by IIIT (Hyderabad) and eight other universities and institutes. To be precise, the beta translation solutions of a few languages will go live next month (June 2009).
The project, whose public Internet interface will be known as Sampark, will let users translate texts among various Indian languages. All one needs to do is copy-paste the text in an appointed box and press ‘enter’, and get the translated version in another box beside it. Not just text, you can translate the whole of a Web page. Copy the URL (a site’s Web address) and paste it in the relevant box in Sampark’s Web site. “You will get the translated page, with photos and other images intact,” says Prof Rajeev Sangal, Director of IIIT (Hyderabad), who is leading the team.
The nine institutions have roped in over 120 experts in computer engineering, language, and translators to take up the ‘machine translation’ programme, which is aimed at breaking the language barrier.
The project is broadly divided into two areas. Translation of the four Southern languages into Hindi (vice versa too) and translation of Bangla, Punjabi, Marathi and Urdu into Hindi (and back). Simultanesouly, the consortium is working on direct translations among Telugu-Tamil, Malayalam-Tamil. To begin with, the consortium has put two ‘systems’ Punjabi-Hindi and Urdu-Hindi beta versions live. “By June 2009 end, we will be adding Tamil-Hindi, Marathi-Hindi and Telugu-Hindi to the project,” Prof Sangal says.
How it works
Broadly, the machine translation happens in three phases — the source side, transfer aspects and the target side action. The two important factors in translation are grammar and dictionary. “Languages have many exceptions and idiosynchrosies. These will be addressed effectively,” Prof Sangal says.
On the source side (the text you want to translate), the machine analyses the text sentence by sentence and keeps a representation of the text. The analysis will include morphological analysis, how words are formed. It will check whether the text carries any local phrases. It will search for nouns and parts of speech before going for sentence analysis.
In the second phase (transfer phase), the machine does lexical and grammar transfer. “The grammars of source and target languages may not be similar. This phase would see change of grammatical structure. The later phase would involve target language generation.”
common architecture
The step-by-step process is done on a common architecture. This allows for addition of a new language to the project quite easily. “If you want to add Kashmiri, you need to develop an analyser, generator and add a Kashmiri-Hindi dictionary. These, in fact, are parallel dictionaries,” Prof Sangal says.
“The project, unlike earlier projects, hinges on dictionaries that give meanings based on concepts rather than just meanings,” Prof Uma Maheshwar Rao, who is working on the Telugu-Hindi aspect of the project, says.
Formed by the Union Ministry of Information Technology in 2006, the consortium comprises IITs (Kharagpur and Bombay), Anna University, C-DAC, University of Hyderabad, Tamil University Jadhavpur University, IISC (Bangalore) and IIIT (Allahabad).
Prof Rao, who works at the Centre of Applied Linguistics and Translation Studies at University of Hyderabad, says the Sampark project is more advanced than earlier attempts that sought to offer translation solutions.
The earlier efforts failed to take the meanings of the words contextually. Citing the example of the word ‘bank’, he points out that the earlier efforts would not make out whether it was a bank used in the expression river bank, or a bank that deals with money.
“In the present project, we cross-link words with all the synonyms in the other language. This will help resolve the ambiguity problem, the knottiest one in the translation process,” he explains.
The immediate task of the consortium is to add more servers and more engineering to make the machine faster.
“We are going to add three languages to the system every two months till November,” Prof Sangal says.
He, however, admits that it is not a complete translator. But the beta versions will definitely give a flavour of the meaning in the source language. You can see improvements constantly, he adds.
Machines learn!
Prof Sangal says the machine can learn based on the data you give it. Look at the sentence — The Chair chairs the meeting. How will a machine understand this sentence? The one developed by the consortium, thanks to the conceptual dictionary, would look at the context and tell apart the meaning of the two chairs in the sentence. “Earlier, we used to give rules to the machine to follow. Now, we have algorithms to let the machines learn from this. We have combined artificial intelligence approach with the linguistic process,” he explains.
More to come
Busy finalising modules, the team members continue to set their eyes on long-term goals. “We will continue the long-term research independently and collaboratively. The next stage is to build more robust sentence analysers. They will be able to do translations more correctly. The quality of the output will go up,” he says. Prof Sangal, who has been working on machine translation for the last 25 years, says it is team work that helped the group to give a shape to the machine. “We discussed several issues physically and through mailing groups. We have set up sub groups to address specific issues.”
English to Indian languages
Simultaneously, a different consortium, in which IIIT-H is also a member, is working on translations from English to several Indian languages and back. C-DAC (Pune) is leading the consortium. The researchers take a different approach.
Unlike popular belief, English is a difficult language for the machine to understand. “Unlike Indian languages, there is a high degree of ambiguity. When a machine analyses, it has to do disambiguation, which is a difficult process,” Prof Sangal says. The research team is almost ready with the English-Hindi version, which is in test mode. At a later stage, these two different projects could technically work in tandem and offer users a better translation experience.
kurmanath@thehindu. co.in
http://www.business line.in/cgi- bin/print. pl?file=20090518 50070300. htm&date=2009/05/ 18/&prd=ew&
Research team turns to the “world’s first computational grammarian!”.
http://www.thehindu businessline. com/ew/2009/ 05/18/images/ 2009051850090301 .jpg
K.V. Kurmanath
Panini, the legendary Sanskrit grammarian of 5th century BC, is the world’s first computational grammarian! Panini’s work, Ashtadhyayi (the Eight-Chaptered book), is considered to be the most comprehensive scientific grammar ever written for any language.
According to Prof Rajeev Sangal, Director of IIIT (Hyderabad) and an expert on language computation, Panini’s epic treatise on grammar came to the rescue of language experts in making English unambiguous. English is more difficult (as far as machine translations are concerned) with a high degree of ambiguity.
Some words have different meanings, making the analysis (to facilitate translations) a difficult process. Making it disambiguous is quite a task, where Panini’s principles might be of use.
Ashtadhyayi, the earlier work on descriptive linguistics, consists of 3,959 sutras (or principles). These highly systemised and technical principles, some say, marked the rise of classical Sanskrit.
Sampark, the multi-institute effort launched to produce a translation engine, enabling users to translate tests from English to various languages, will use some of the technical aspects enunciated by Panini. “We looked at alternatives before choosing Panini,” Prof Sangal says.
Incidentally, Prof Sangal co-authored a book, Natural Language Processing – A Panini Perspective, a few years ago.
Besides the technical side, Panini would be of great help to researchers on the translation engine on the language side too.
A good number of words in almost all the Indian languages originate from Sanskrit. “That is great because Indian languages are related to each other,” Prof Sangal points out.
kurmanath@thehindu. co.in
http://www.thehindu businessline. com/ew/2009/ 05/18/stories/ 2009051850090300 .htm
Break the language barrier
Word for word: More on the Sampark initiative to enrich translation. .
Look at the sentence — The Chair chairs the meeting. How will a machine understand this?
http://www.thehindu businessline. com/bline/ ew/2009/05/ 18/images/ 2009051850070301 .jpg
K.V. Kurmanath
Telugus, Kannadigas and Malayalis can read Subrahmanya Bharati, the legendary Tamil poet, and relish the sweetness in his poetry. Similarly, Premchand, Tagore, M T Vasudeva Nair, and U R Ananthamurthy too could be read and understood by readers in other languages.
All this will soon be a reality, thanks to a project initiated by IIIT (Hyderabad) and eight other universities and institutes. To be precise, the beta translation solutions of a few languages will go live next month (June 2009).
The project, whose public Internet interface will be known as Sampark, will let users translate texts among various Indian languages. All one needs to do is copy-paste the text in an appointed box and press ‘enter’, and get the translated version in another box beside it. Not just text, you can translate the whole of a Web page. Copy the URL (a site’s Web address) and paste it in the relevant box in Sampark’s Web site. “You will get the translated page, with photos and other images intact,” says Prof Rajeev Sangal, Director of IIIT (Hyderabad), who is leading the team.
The nine institutions have roped in over 120 experts in computer engineering, language, and translators to take up the ‘machine translation’ programme, which is aimed at breaking the language barrier.
The project is broadly divided into two areas. Translation of the four Southern languages into Hindi (vice versa too) and translation of Bangla, Punjabi, Marathi and Urdu into Hindi (and back). Simultanesouly, the consortium is working on direct translations among Telugu-Tamil, Malayalam-Tamil. To begin with, the consortium has put two ‘systems’ Punjabi-Hindi and Urdu-Hindi beta versions live. “By June 2009 end, we will be adding Tamil-Hindi, Marathi-Hindi and Telugu-Hindi to the project,” Prof Sangal says.
How it works
Broadly, the machine translation happens in three phases — the source side, transfer aspects and the target side action. The two important factors in translation are grammar and dictionary. “Languages have many exceptions and idiosynchrosies. These will be addressed effectively,” Prof Sangal says.
On the source side (the text you want to translate), the machine analyses the text sentence by sentence and keeps a representation of the text. The analysis will include morphological analysis, how words are formed. It will check whether the text carries any local phrases. It will search for nouns and parts of speech before going for sentence analysis.
In the second phase (transfer phase), the machine does lexical and grammar transfer. “The grammars of source and target languages may not be similar. This phase would see change of grammatical structure. The later phase would involve target language generation.”
common architecture
The step-by-step process is done on a common architecture. This allows for addition of a new language to the project quite easily. “If you want to add Kashmiri, you need to develop an analyser, generator and add a Kashmiri-Hindi dictionary. These, in fact, are parallel dictionaries,” Prof Sangal says.
“The project, unlike earlier projects, hinges on dictionaries that give meanings based on concepts rather than just meanings,” Prof Uma Maheshwar Rao, who is working on the Telugu-Hindi aspect of the project, says.
Formed by the Union Ministry of Information Technology in 2006, the consortium comprises IITs (Kharagpur and Bombay), Anna University, C-DAC, University of Hyderabad, Tamil University Jadhavpur University, IISC (Bangalore) and IIIT (Allahabad).
Prof Rao, who works at the Centre of Applied Linguistics and Translation Studies at University of Hyderabad, says the Sampark project is more advanced than earlier attempts that sought to offer translation solutions.
The earlier efforts failed to take the meanings of the words contextually. Citing the example of the word ‘bank’, he points out that the earlier efforts would not make out whether it was a bank used in the expression river bank, or a bank that deals with money.
“In the present project, we cross-link words with all the synonyms in the other language. This will help resolve the ambiguity problem, the knottiest one in the translation process,” he explains.
The immediate task of the consortium is to add more servers and more engineering to make the machine faster.
“We are going to add three languages to the system every two months till November,” Prof Sangal says.
He, however, admits that it is not a complete translator. But the beta versions will definitely give a flavour of the meaning in the source language. You can see improvements constantly, he adds.
Machines learn!
Prof Sangal says the machine can learn based on the data you give it. Look at the sentence — The Chair chairs the meeting. How will a machine understand this sentence? The one developed by the consortium, thanks to the conceptual dictionary, would look at the context and tell apart the meaning of the two chairs in the sentence. “Earlier, we used to give rules to the machine to follow. Now, we have algorithms to let the machines learn from this. We have combined artificial intelligence approach with the linguistic process,” he explains.
More to come
Busy finalising modules, the team members continue to set their eyes on long-term goals. “We will continue the long-term research independently and collaboratively. The next stage is to build more robust sentence analysers. They will be able to do translations more correctly. The quality of the output will go up,” he says. Prof Sangal, who has been working on machine translation for the last 25 years, says it is team work that helped the group to give a shape to the machine. “We discussed several issues physically and through mailing groups. We have set up sub groups to address specific issues.”
English to Indian languages
Simultaneously, a different consortium, in which IIIT-H is also a member, is working on translations from English to several Indian languages and back. C-DAC (Pune) is leading the consortium. The researchers take a different approach.
Unlike popular belief, English is a difficult language for the machine to understand. “Unlike Indian languages, there is a high degree of ambiguity. When a machine analyses, it has to do disambiguation, which is a difficult process,” Prof Sangal says. The research team is almost ready with the English-Hindi version, which is in test mode. At a later stage, these two different projects could technically work in tandem and offer users a better translation experience.
kurmanath@thehindu. co.in
http://www.business line.in/cgi- bin/print. pl?file=20090518 50070300. htm&date=2009/05/ 18/&prd=ew&
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