Ananthakrishnan Ramanathan

Case markers and Morphology: Addressing the crux of the fluency problem in English-Hindi SMT

We report in this paper our work on accurately generating case markers and suffixes in English-to-Hindi SMT. Hindi is a relatively free word-order language, and makes use of a comparatively richer set of case markers and morphological suffixes for correct meaning representation. From our experience of large-scale English-Hindi MT, we are convinced that fluency and fidelity in the Hindi output get an order of magnitude facelift if accurate case markers and suffixes are produced. Now, the moot question is: what entity on the English side encodes the information contained in case markers and suffixes on the Hindi side? Our studies of correspondences in the two languages show that case markers and suffixes in Hindi are predominantly determined by the combination of suffixes and semantic relations on the English side. We, therefore, augment the aligned corpus of the two languages, with the correspondence of English suffixes and semantic relations with Hindi suffixes and case markers. Our results on 400 test sentences, translated using an SMT system trained on around 13000 parallel sentences, show that suffix + semantic relation → case marker/suffix is a very useful translation factor, in the sense of making a significant difference to output quality as indicated by subjective evaluation as well as BLEU scores.

Concentration in Knowledge Output: A Case of Economics Journals

This paper assesses the degree of author concentration in seven economics journals, which were published in India during 1990-2002. To measure the degree of author concentration, Lotkas Law was used. Moreover, we also make an exploratory analysis of the geographic, economics subfield and institutional concentration in 704 economics journals. An important finding of this paper is that specialized journals in the sample report the highest degree of author concentration. This result is quite similar to the findings by Cox and Chung (1991). Furthermore, there are several instances showing that the journals lean towards certain norms; this may affect the flow of innovative ideas into economics. We conclude that a knowledge activity, involving the high degree of concentration and a biased publication process, may affect the flow of new ideas into the discipline.

Offering language based services on social media by identifying user's preferred language(s) from romanized text

With the increase of multilingual content and multilingual users on the web, it is prudent to offer personalized services and ads to users based on their language profile (\textit{i.e.}, the list of languages that a user is conversant with). Identifying the language profile of a user is often non-trivial because (i) users often do not specify all the languages known to them while signing up for an online service (ii) users of many languages (especially Indian languages) largely use Latin/Roman script to write content in their native language. This makes it non-trivial for a machine to distinguish the language of one comment from another. This situation presents an opportunity for offering following language based services for romanized content (i) hide romanized comments which belong to a language which is not known to the user (ii) translate romanized comments which belong to a language which is not known to the user (iii) transliterate romanized comments which belong to a language which is known to the user (iv) show language based ads by identifying languages known to a user based on the romanized comments that he wrote/read/liked. We first use a simple bootstrapping based semi-supervised algorithm for identify the language of a romanized comment. We then apply this algorithm to all the comments written/read/liked by a user to build a language profile of the user and propose that this profile can be used to offer the services mentioned above.