ﻻ يوجد ملخص باللغة العربية
Understanding and being able to react to customer feedback is the most fundamental task in providing good customer service. However, there are two major obstacles for international companies to automatically detect the meaning of customer feedback in a global multilingual environment. Firstly, there is no widely acknowledged categorisation (classes) of meaning for customer feedback. Secondly, the applicability of one meaning categorisation, if it exists, to customer feedback in multiple languages is questionable. In this paper, we extracted representative real world samples of customer feedback from Microsoft Office customers in multiple languages, English, Spanish and Japanese,and concluded a five-class categorisation(comment, request, bug, complaint and meaningless) for meaning classification that could be used across languages in the realm of customer feedback analysis.
E-commerce stores collect customer feedback to let sellers learn about customer concerns and enhance customer order experience. Because customer feedback often contains redundant information, a concise summary of the feedback can be generated to help
In this paper, we introduce ``Embedding Barrier, a phenomenon that limits the monolingual performance of multilingual models on low-resource languages having unique typologies. We build `BanglaBERT, a Bangla language model pretrained on 18.6 GB Inter
Multimodal pre-training with text, layout, and image has achieved SOTA performance for visually-rich document understanding tasks recently, which demonstrates the great potential for joint learning across different modalities. In this paper, we prese
Multilingual pretrained language models have demonstrated remarkable zero-shot cross-lingual transfer capabilities. Such transfer emerges by fine-tuning on a task of interest in one language and evaluating on a distinct language, not seen during the
This paper concerns the intersection of natural language and the physical space around us in which we live, that we observe and/or imagine things within. Many important features of language have spatial connotations, for example, many prepositions (l