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Sound-based distributional models

• Alessandro Lopopolo, Emiel van Miltenburg
• IWCS
• 2015

Following earlier work in multimodal distributional semantics, we present the first results of our efforts to build a perceptually grounded semantic model. Rather than using images, our models are built on sound data collected from freesound.org. We compare three models: one bag-of-words model based on user-provided tags, a model based on audio features,… (More)

Stereotyping and Bias in the Flickr30K Dataset

• Emiel van Miltenburg
• ArXiv
• 2016

In: Proceedings of the Workshop on Multimodal Corpora: Computer vision and language processing (MMC-2016), pages 1–4. An untested assumption behind the crowdsourced descriptions of the images in the Flickr30K dataset (Young et al., 2014) is that they " focus only on the information that can be obtained from the image alone " (Hodosh et al., 2013, p. 859).… (More)

Pragmatic Factors in Image Description: The Case of Negations

• Emiel van Miltenburg, Roser Morante, Desmond Elliott
• VL@ACL
• 2016

We provide a qualitative analysis of the descriptions containing negations (no, not, n't, nobody, etc) in the Flickr30K corpus , and a categorization of negation uses. Based on this analysis, we provide a set of requirements that an image description system should have in order to generate negation sentences. As a pilot experiment, we used our… (More)

Detecting and ordering adjectival scalemates

• Emiel van Miltenburg
• ArXiv
• 2015

This paper presents a pattern-based method that can be used to infer adjectival scales, such as lukewarm,warm, hot, from a corpus. Specifically , the proposed method uses lexical patterns to automatically identify and order pairs of scale-mates, followed by a filtering phase in which unrelated pairs are discarded. For the filtering phase, several different… (More)

The VU Sound Corpus: Adding More Fine-grained Annotations to the Freesound Database

• Emiel van Miltenburg, Benjamin Timmermans, Lora Aroyo
• LREC
• 2016

Pragmatic descriptions of perceptual stimuli

• Emiel van Miltenburg
• 2017

This research proposal discusses pragmatic factors in image description, arguing that current automatic image description systems do not take these factors into account. I present a general model of the human image description process, and propose to study this process using corpus analysis, experiments, and computational modeling. This will lead to a… (More)

Building a Dictionary of Affixal Negations

• Chantal van Son, Emiel van Miltenburg, Roser Morante
• 2016

This paper discusses the need for a dictionary of affixal negations and regular antonyms to facilitate their automatic detection in text. Without such a dictionary, affixal negations are very difficult to detect. In addition, we show that the set of affixal negations is not homogeneous, and that different NLP tasks may require different subsets. A… (More)

Room for improvement in automatic image description: an error analysis

• Emiel van Miltenburg, Desmond Elliott
• ArXiv
• 2017

In recent years we have seen rapid and significant progress in automatic image description but what are the open problems in this area? Most work has been evaluated using text-based similarity metrics, which only indicate that there have been improvements, without explaining what has improved. In this paper, we present a detailed error analysis of the… (More)

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