A benchmark of Spanish language datasets for computationally driven research

In the domain of Galleries, Libraries, Archives and Museums (GLAM) institutions, creative and innovative tools and methodologies for content delivery and user engagement have recently gained international attention. New methods have been proposed to publish digital collections as datasets amenable to computational use. Standardised benchmarks can be useful to broaden the scope of machine-actionable collections and to promote cultural and linguistic diversity. In this article, we propose a methodology to select datasets for computationally driven research applied to Spanish text corpora. This work seeks to encourage Spanish and Latin American institutions to publish machine-actionable collections based on best practices and avoiding common mistakes.

The translation of images and West Indian creole into Spanish in Sam Selvon’s The Lonely Londoners

Sam Selvon’s The Lonely Londoners is considered a classic of West Indian literature in the style of Migrant Modernism (Brown 2013). First published in post-war London in 1956, it was not translated into Spanish until 2016, probably due to the challenging features of the novel and its language. A case of text creolisation (Buzelin 2000), the translation of the novel required an active effort to construct a language variant that could convey Selvon’s peculiar literary style and sociopolitical intent. The present work aims to investigate the images of West Indians portrayed in the original novel and, more specifically, how they are transposed into the Spanish text. The research method includes an account of the editorial process, an interview with the translator, and an analysis of the paratexts and translation excerpts. Finally, the reception of the translation in literary reviews shall also be discussed.

Impact of cultural-shift on multimodal sentiment analysis

Human communication is not limited to verbal speech but is infinitely more complex, involving many non-verbal cues such as facial emotions and body language. This paper aims to quantitatively show the impact of non-verbal cues, with primary focus on facial emotions, on the results of multi-modal sentiment analysis. The paper works with a dataset of Spanish video reviews. The audio is available as Spanish text and is translated to English while visual features are extracted from the videos. Multiple classification models are made to analyze the sentiments at each modal stage i.e. for the Spanish and English textual datasets as well as the datasets obtained upon coalescing the English and Spanish textual data with the corresponding visual cues. The results show that the analysis of Spanish textual features combined with the visual features outperforms its English counterpart with the highest accuracy difference, thereby indicating an inherent correlation between the Spanish visual cues and Spanish text which is lost upon translation to English text.

How Many Collocations do Heritage Speakers Know?

The current study examines a previously understudied dimension of heritage speakers’ lexical knowledge by focusing on verbal collocations. Two tests were designed in order to assess both receptive (recognition) and productive (recall) knowledge of sixty Spanish collocations. The collocations were divided into three types (congruent, partially congruent, and incongruent) based on a ratings survey that established their degree of correspondence with English. Participants’ language dominance and their use of Spanish in various daily activities were included as individual variables. The results indicate that the participants knew a vast majority of the collocations on the recognition test, but that their ability to recall the collocations was somewhat more limited. Congruency had a significant effect on participants’ performance, but this finding must be interpreted in light of the interaction between congruency and word frequency. Significant correlations were found between performance on both tests and language dominance, as well as a number of variables involving interaction in Spanish (text messaging) and exposure (listening to music, reading for fun). These data are discussed in relation to previous studies on the acquisition of collocations and heritage speakers’ knowledge of individual words.

Pronominal Anaphora Resolution on Spanish Text

Recent technological advances have allowed the development of numerous natural language processing applications with which users frequently interact. When interacting with this type of application, users often search for the economy of words, which promotes the use of pronouns, thereby highlighting the well-known anaphora problem. This chapter describes a proposal to approach the pronominal anaphora for the Spanish language. A set of rules (based on the Eagle standard) was designed to identify the referents of personal pronouns through the structure of the grammatical tags of the words. The proposed algorithm uses the online Freeling service to perform tokenization and tagging tasks. The performance of the algorithm was compared with an online version of Freeling, and the proposed algorithm shows better performance.

A gesture recognition system for the Colombian sign language based on convolutional neural networks

Sign languages (or signed languages) are languages that use visual techniques, primarily with the hands, to transmit information and enable communication with deaf-mutes people. This language is traditionally only learned by people with this limitation, which is why communication between deaf and non-deaf people is difficult. To solve this problem we propose an autonomous model based on convolutional networks to translate the Colombian Sign Language (CSL) into normal Spanish text. The scheme uses characteristic images of each static sign of the language within a base of 24000 images (1000 images per category, with 24 categories) to train a deep convolutional network of the NASNet type (Neural Architecture Search Network). The images in each category were taken from different people with positional variations to cover any angle of view. The performance evaluation showed that the system is capable of recognizing all 24 signs used with an 88% recognition rate.

Decision Algorithm for the Automatic Determination of the Use of Non-Inclusive Terms in Academic Texts

The use of inclusive language, among many other gender equality initiatives in society, has garnered great attention in recent years. Gender equality offices in universities and public administration cannot cope with the task of manually checking the use of non-inclusive language in the documentation that those institutions generate. In this research, an automated solution for the detection of non-inclusive uses of the Spanish language in doctoral theses generated in Spanish universities is introduced using machine learning techniques. A large dataset has been used to train, validate, and analyze the use of inclusive language; the result is an algorithm that detects, within any Spanish text document, non-inclusive uses of the language with error, false positive, and false negative ratios slightly over 10%, and precision, recall, and F-measure percentages over 86%. Results also show the evolution with time of the ratio of non-inclusive usages per document, having a pronounced reduction in the last years under study.

The identity of Azara´s (1805) No. 246 Trepador remos y cola roxos (Aves: Furnariidae)

The identity of Azara’s No. 246 “Trepador remos y cola roxos” and the names Dendrocolaptes miniatus Illiger, 1820 and Dendrocopus rubricaudatus Vieillot, 1818, which are based on it, have never been convincingly elucidated, and previously proposed identifications in the literature are demonstrably incorrect. Azara shot his specimen in a Paraguayan forest and provided a detailed description and measurements of it in his Spanish text. These are sufficient to confirm the identity of the specimen and the names based on it as the Olive Spinetail, long known as Cranioleuca obsoleta (Reichenbach, 1853). Dendrocolaptes miniatus Illiger, 1820 and Dendrocopus rubricaudatus Vieillot, 1818 nevertheless have date priority over that name, but as they have not been used as valid since 1899 they are nomina oblita under Article 23.9.2 of the Code. Cranioleuca obsoleta has been in universal use for this species since Hellmayr (1925), so it qualifies as a nomen protectum under Article 23.9.2, and remains the valid name for the Olive Spinetail.