Articles

Beyond the generic activities (cataloguing, producing, distribution of Language Resources, dissemination of information, etc.) that make the overall ELRA mission an indispensable middle-man in the field of Language Resources (LRs), new directions of work are now being undertaken so as to answer the needs of this ever-moving community. This impacts …...

Summarization corpora are numerous but fragmented, making it challenging for researchers to efficiently pinpoint corpora most suited to a given summarization task. In this paper, we introduce a repository containing corpora available to train and evaluate automatic summarization systems. We also present an overview of the main corpora with respect …...

Summarization of multi-party conversation is one of the important tasks in natural language processing. For conversation summarization tasks, corpora have an important role to analyze characteristics of conversations and to construct a method for summary generation. We are developing a freely available Japanese conversation corpus for a decision-making task. We …...

The need for cross-lingual information access is more than ever with the easy accessibility to the Internet, especially in vastly multilingual societies like India. Cross-lingual summarization can help minimize human effort needed for achieving publishable articles in multiple languages, while making the most important information available in target language in …...

We present a new dataset for tweet summarization. The dataset includes six events collected from Twitter from October 10 to November 9, 2016. Our dataset features two prominent properties. Firstly, human-annotated gold-standard references allow to correctly evaluate extractive summarization methods. Secondly, tweets are assigned into sub-topics divided by consecutive days, …...

Commonsense knowledge as provided by scripts is crucially relevant for text understanding systems, providing a basis for commonsense inference. This paper considers a relevant subtask of script-based text understanding, the task of mapping event mentions in a text to script events. We focus on script representations where events are associated …...

The pyramid method is a content analysis approach in automatic summarization evaluation for manual construction of a content model from reference summaries, and manual scoring of unseen summaries with the pyramid model. PyrEval automates the manual pyramid method. PyrEval uses low-dimension distributional semantics to represent phrase meanings, and a new …...

Multi-sentence compression aims to generate a short and informative compression from several source sentences that deal with the same topic. In this work, we present a new corpus for the Multi-Sentence Compression (MSC) task in Portuguese and Spanish. We also provide on this corpus a comparison of two state-of-the-art MSC …...

Automatic summarization has so far focused on datasets of ten to twenty rather short documents, typically news articles. But automatic systems could in theory analyze hundreds of documents from a wide range of sources and provide an overview to the interested reader. Such a summary would ideally present the most …...

The motivation for this paper is to present a way to verify if an utterance within a corpus is pronounced at a fast or slow pace. An alternative method to the well-known Word-Per-Minute (wpm) method for cases where this approach is not applicable. For long segmentations, such as the full...

This paper investigates speaker adaptation techniques for bidirectional long short term memory (BLSTM) recurrent neural network based acoustic models (AMs) trained with the connectionist temporal classification (CTC) objective function. BLSTM-CTC AMs play an important role in end-to-end automatic speech recognition systems. However, there is a lack of research in speaker …...

We present a new workflow to create components for the MaryTTS text-to-speech synthesis platform, which is popular with researchers and developers, extending it to support new languages and custom synthetic voices. This workflow replaces the previous toolkit with an efficient, flexible process that leverages modern build automation and cloud-hosted infrastructure. …...

Automatic speech recognition is a requested technique in many fields like automatic subtitling, dialogue systems and information retrieval systems. The training of an automatic speech recognition system is usually straight forward given a large annotated speech corpus for acoustic modeling, a phonetic lexicon, and a text corpus for the training …...

Live blogs are an increasingly popular news format to cover breaking news and live events in online journalism. Online news websites around the world are using this medium to give their readers a minute by minute update on an event. Good summaries enhance the value of the live blogs for …...

Discriminating between similar languages (DSL) on conversational texts is a challenging task. This paper aims at discriminating between limited-resource languages on short conversational texts, like Uyghur and Kazakh. Considering that Uyghur and Kazakh data are severely imbalanced, we leverage an effective compensation strategy to build a balanced Uyghur and Kazakh …...

Neural network-based dialog systems are attracting increasing attention in both academia and industry. Recently, researchers have begun to realize the importance of speaker modeling in neural dialog systems, but there lacks established tasks and datasets. In this paper, we propose speaker classification as a surrogate task for general speaker modeling, …...

Long Short-Term Memory (LSTM) and its variants have been the standard solution to sequential data processing tasks because of their ability to preserve previous information weighted on distance. This feature provides the LSTM family with additional information in predictions, compared to regular Recurrent Neural Networks (RNNs) and Bag-of-Words (BOW) models. …...

This paper describes different approaches to improve the transcription and indexing quality of the Fraunhofer IAIS Audio Mining system on Oral History interviews for the Digital Humanities Research. As an essential component of the Audio Mining system, automatic speech recognition faces a lot of difficult challenges when processing Oral History …...

Developing language resources is an important task when creating a speech recognition system for a less-resourced language. In this paper we describe available language resources and their preparation for use in a large vocabulary speech recognition (LVSR) system for Icelandic. The content of a speech corpus is analysed and training …...

This paper presents an approach to simulate automatic speech recognition (ASR) errors from manual transcriptions and describes how it can be used to improve the performance of spoken language understanding (SLU) systems. In particular, we point out that this noising process is very usefull to obtain a more robust SLU …...