The auxiliary verb in Eastern Armenian is a clitic that carries tense and agreement and is used to form all the indicative forms of the verb with the exception of the aorist tense. Discover what this means for Persian and multilingual, low‑resource NLP.

Provides insights into effective digital marketing strategies for small businesses. Learn what the authors found and why it matters.

This report provides guidelines for transcribing Pashto, as part of the NIST evaluation projects on machine translation (GALE) and speech translation in real-world tactical situations (TRANSTAC). Read for methods, evaluations, and why the findings matter for scalable AI systems.

This paper describes a two-level morphological analyzer for Persian using a system based on the Xerox finite state tools. Discover what this means for Persian and multilingual, low‑resource NLP.

This talk presented information about existing computer tools that can be used by Persian language teachers in the classroom or by Persian language learners who are doing research, preparing reports, or doing exercises. Discover what this means for Persian and multilingual, low‑resource NLP.

No abstract available. Learn what the authors found and why it matters.

There exists a continuing debate in the field of foreign language teaching on the relative viability of implicit vs. Discover what this means for Persian and multilingual, low‑resource NLP.

No abstract available. Learn what the authors found and why it matters.

A review of sentiment lexicons, as of 2010. Learn what the authors found and why it matters.

The exponential growth of the Persian blogosphere and the increased number of neologisms create a major challenge in NLP applications of Persian blogs. Discover what this means for Persian and multilingual, low‑resource NLP.

This paper presents research on the feasibility and development of methods for the rapid creation of stopgap language technology resources for low-density languages. Discover what this means for Persian and multilingual, low‑resource NLP.

With vast amounts of information currently available digitally, it is difficult to sift through the data and discover important details. Read for methods, evaluations, and why the findings matter for scalable AI systems.