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IBM seeks to burnish its machine translation solution with a “human” touch

The software giant is improving translations of his expected n.Fluent aimed at instant messaging with the help of thousands of employees. The system converts text in real time and is being tested internally.

Using a series of crowdsourcing strategies and events, IBM’s n.Fluent has managed to successfully engage and nurture an active, multinational pool of volunteer translators, who are dedicated to innovation.  This is just one of the strategies IBM will use to add the “human” touch in its announced, and soon to be released machine translation solution. The tool seeks to become an important channel for communication between different languages in instant messaging systems, commercially and socially.

The IBM statement is important for the translation and localization community, “one key cornerstones of the n.Fluent project is its Crowdsourcing strategy-which enables us to effectively tap into the collective power of bilingual IBMers for translating sentences or correcting machine translated sentences-for improving translation accuracy and quality.”

Indoors, a team of about a hundred people including developers, linguists and mathematicians, are working to shape a comprehensive program for Internet machine translation that will be useful for sites and documents, but especially for IM.

The system is supposed to support languages including translations into English, Spanish, French, German, Italian, Japanese, Arabic, Chinese, Korean, Portuguese and Russian.

Now, tucked into the last stage of development, the multinational company with headquarters in New York is looking for that little “human” touch for n.Fluent.  The human touch will come from the contributions and comments to the translations that are being analyzed and corrected by the company’s own employees, (IBM has about 400,000 in nearly 161 countries), in an effort to refine the computing work done by the servers.

According to The New York Times, the n.Fluent was launched internally a year ago. It now counts on massive amounts of parallel data as around 3,000 crowdsourcing volunteers have collectively contributed about 36Million words (crowdsourcing from instant message chats and crowdsourcing translations). This is expected to provide further improvements in accuracy, meaning and quality, and programmers will seek that the machines “learn” the most accurate expressions for each language.

IBM is the world’s largest IT services company, with revenues of 103,600 million dolars last year.