In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Input: Consider Input: This article describes the systems jointly submitted by Institute for Infocomm (IR), the Laboratoire d'Informatique de l'Universit du Maine (LIUM), Nanyang Technology University (NTU) and the University of Eastern Finland (UEF) for 2015 NIST Language Recognition Evaluation (LRE). The submitted system is a fusion of nine sub-systems based on i-vectors [1] extracted from different types of features. Given the i-vectors, several classifiers are adopted for the language detection task including support vector machines (SVM) [2], multi-class logistic regression (MCLR), Probabilistic Linear Discriminant Analysis (PLDA) [3] and Deep Neural Networks (DNN).

Output: Fantastic 4 system for NIST 2015 Language Recognition Evaluation

Input: Consider Input: This paper is motivated by the automation of neuropsychological tests involving discourse analysis in the retellings of narratives by patients with potential cognitive impairment. In this scenario the task of sentence boundary detection in speech transcripts is important as discourse analysis involves the application of Natural Language Processing tools, such as taggers and parsers, which depend on the sentence as a processing unit. Our aim in this paper is to verify which embedding induction method works best for the sentence boundary detection task, specifically whether it be those which were proposed to capture semantic, syntactic or morphological similarities.

Output: Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts

Input: Consider Input: In this age of information technology, information access in a convenient manner has gained importance. Since speech is a primary mode of communication among human beings, it is natural for people to expect to be able to carry out spoken dialogue with computer [1]. Speech recognition system permits ordinary people to speak to the computer to retrieve information. It is desirable to have a human computer dialogue in local language. Hindi being the most widely spoken Language in India is the natural primary human language candidate for human machine interaction. There are five pairs of vowels in Hindi languages; one member is longer than the other one. This paper describes an overview of speech recognition system. How speech is produced and the properties and characteristics of Hindi
Output: AN OVERVIEW OF HINDI SPEECH RECOGNITION