Automatic Text Summarization (ATS) is a Natural Language Processing (NLP) task essential for handling large volumes of information. ATS can be classified into two main types: extractive and abstractive. Extract
Automatic text summarization: A comprehensive survey Expert Systems with Applications (2021) FangS.-H.et al. Detection of pathological voice using cepstrum vectors: A deep learning approach Journal of Voice (2019) LandiniF.et al. Bayesian HMM clustering of x-vector sequences (VBx) in speaker di...
Figure4a illustrates the comparative analysis of model performances through relative ratings. Notably, MMed-Llama 3 achieved the highest scores in both human (4.10) and GPT-4 (4.73) evaluations, aligning with its superior performance as indicated by the automatic machine metrics. It is particularly ...
creation of a community of researchers from diverse fields, such as computer and social sciences, as well as policy makers and other stakeholders interested in automatic counterspeech generation. By doing so we aim to gain a deeper understanding of how counterspeech is currently used to tackle ...
The Question Generation (QG) task is one of the main Natural Language Processing (NLP) problems, and it is defined as the automatic generation of questions from inputs such as text, raw data and knowledge bases1. Specifically, an answer-aware Question Generation system performs the QG task gi...
BUFFET. It unifies 15 diverse NLP datasets in typologically diverse 54 languages. PolyglotPrompt. The dataset covers six tasks - topic classification, sentiment classification, named entity recognition, question answering, natural language inference, and summarization - across 49 languages. ...
In this paper, we seek to explore whether senses aligned across languages exhibit this trait consistently, and if this is the case, we investigate how this property can be leveraged in an automatic fashion. We first conduct a manual annotation study to gauge whether the subjectivity trait of a...
developed within the EU-funded project MUMIS that support automatic indexing of multimedia recordings and retrieval of indexed multimedia archives [Declerck and Wittenburg, 2001]. The test domains of MUMIS are Soccer Games, e.g., the UEFA 2000 and ...
This multi lingual key terms extraction system for Hindi and Punjabi will be very much helpful for developing other NLP resources in Hindi and Punjabi like: automatic text summarization, document classification, document clustering, question answering and topic tracking etc. The overall Precision and ...
as disclosed in more detail below. The modules further include one or more functional modules19that can include the additional functionality, such as modules for performing NLP tasks such as automatic summarization, coreference resolution, discourse analysis, machine translation, morphological segmentation,...