Applying feature reduction analysis to a PPRLM-multiple Gaussian language identification system

This paper presents the application of a feature selection technique such as LDA to a language identification (LID) system. The baseline system consists of a PPRLM module followed by a multiple-Gaussian classifier. This classifier makes use of acoustic scores and duration features of each input utterance. We applied a dimension reduction of the feature space in order to achieve a faster and easier-trainable system. We imputed missing values of our vectors before projecting them on the new space. Our experiments show a very low performance reduction due to the dimension reduction approach. Using a single dimension projection the error rates we have obtained are about 8.73% taking into account the 22 most significant features

Parálisis cerebral y sistemas de seguimiento de la mirada: ¿clic por parpadeo o permanencia?

Los comandos básicos para el control de ordenadores a través de interfaces gráficas son comandos de alcance a un objeto en pantalla y su selección. El presente documento describe un estudio comparativo a nivel funcional de dos estrategias de selección alternativas, especialmente diseñada para personas con parálisis cerebral: clic por permanencia y clic por parpadeo, mientras que la tarea de alcance se realiza a través de movimientos oculares

SD-TEAM: Interactive Learning, Self-Evaluation and Multimodal Technologies for Multidomain Spoken Dialog Systems

Speech technology currently supports the development of dialogue systems that function in limited domains for which they were trained and in conditions for which they were designed, that is, specific acoustic conditions, speakers etc. The international scientific community has made significant efforts in exploring methods for adaptation to different acoustic contexts, tasks and types of user. However, further work is needed to produce multimodal spoken dialogue systems capable of exploiting interactivity to learn online in order to improve their performance. The goal is to produce flexible and dynamic multimodal, interactive systems based on spoken communication, capable of detecting automatically their operating conditions and especially of learning from user interactions and experience through evaluating their own performance. Such ?living? systems will evolve continuously and without supervision until user satisfaction is achieved. Special attention will be paid to those groups of users for which adaptation and personalisation is essential: amongst others, people with disabilities which lead to communication difficulties (hearing loss, dysfluent speech, ...), mobility problems and non-native users. In this context, the SD-TEAM Project aims to advance the development of technologies for interactive learning and evaluation. In addition, it will develop flexible distributed architectures that allow synergistic interaction between processing modules from a variety of dialogue systems designed for distinct tasks, user groups, acoustic conditions, etc. These technologies will be demonstrated via multimodal dialogue systems to access to services from home and to access to unstructured information, based on the multi-domain systems developed in the previous project TIN2005-08660-C04

Rooting big and deep rapidly: the ecological roots of pine species distribution in southern Europe

Root properties can influence plant drought resistance, and consequently plant species distribution. Root structure strongly varies across biomes partly as a result of phylogeny. However, whether the spatial distribution of phylogenetically close plant species is linked to differences in root properties remains unclear. We examined whether root properties mediate the strong correlation between summer drought intensity and the spatial segregation of pine species native to southern Europe. For this, we compared the seedling root growth and structure of five ecologically distinct pine species grown in 360 L rhizotrons for 19 months under typical hot and dry Mediterranean conditions. We studied the mountain and boreo-alpine pines Pinus sylvestris and Pinus nigra, and the Mediterranean pines Pinus pinaster, Pinus pinea, and Pinus halepensis. Mediterranean pines formed deep roots faster than mountain pines, their shoots and roots grew faster and had higher root growth, especially P. halepensis, at low air temperature. By the end of the study, Mediterranean pines had larger root systems than mountain pines. Neither distribution of root mass with depth nor root-to-shoot mass ratio varied significantly among species. Across species, minimal annual rainfall to which species are exposed in their range related negatively to root growth but positively to specific root length and the time needed for roots to reach a depth of 40 cm. This study highlights the importance of root growth as a driver of pine distribution in southern Europe and suggests that rapidly producing a large, deep root system may be a key attribute for pines to colonize dry Mediterranean locations.info:eu-repo/semantics/acceptedVersio

Language recognition using phonotactic-based shifted delta coefficients and multiple phone recognizers

A new language recognition technique based on the application of the philosophy of the Shifted Delta Coefficients (SDC) to phone log-likelihood ratio features (PLLR) is described. The new methodology allows the incorporation of long-span phonetic information at a frame-by-frame level while dealing with the temporal length of each phone unit. The proposed features are used to train an i-vector based system and tested on the Albayzin LRE 2012 dataset. The results show a relative improvement of 33.3% in Cavg in comparison with different state-of-the-art acoustic i-vector based systems. On the other hand, the integration of parallel phone ASR systems where each one is used to generate multiple PLLR coefficients which are stacked together and then projected into a reduced dimension are also presented. Finally, the paper shows how the incorporation of state information from the phone ASR contributes to provide additional improvements and how the fusion with the other acoustic and phonotactic systems provides an important improvement of 25.8% over the system presented during the competition

Water relations and vulnerability to embolism are not related: Experiments with eight grapevine cultivars

Drought tolerance mechanisms at the leaf level have been reported for grapevines but less is known about their vulnerability to embolism caused by water stress. The objective of this experiment was to determine if there is a relationship between xylem hydraulic characteristics and drought resistance mechanisms at the leaf level. The experiment was carried out on 10-year-old plants of 8 V. vinifera cvs: 'Sauvignon Blanc', 'Chardonnay', 'Cabernet Sauvignon', 'White Grenache', 'Black Grenache', 'Alicante Bouschet', 'Tempranillo', and 'Parellada' grown under field conditions without irrigation under Mediterranean climatic conditions. Embolism vulnerability curves were drawn for each cultivar. Values of the osmotic potential at full turgor, and at the turgor loss point, and the leaf bulk modulus of elasticity were obtained from pressure-volume curves on 4 different dates, from berries at pea size until harvest. All cultivars except 'Chardonnay', which showed elastic adjustment, showed osmoregulation but different patterns in vulnerability curves were found for each cultivar. While 'Parellada', 'Tempranillo' and 'Black Grenache' proved to have the most vulnerable xylem, 'Chardonnay' and 'Sauvignon Blanc' were shown to have the least vulnerable xylem to embolism. There was no relationship between the level of vulnerability to embolism for each cultivar and the drought tolerance mechanisms at the leaf level under the environmental conditions of this experiment. &nbsp

Advanced Speech Communication System for Deaf People

This paper describes the development of an Advanced Speech Communication System for Deaf People and its field evaluation in a real application domain: the renewal of Driver’s License. The system is composed of two modules. The first one is a Spanish into Spanish Sign Language (LSE: Lengua de Signos Española) translation module made up of a speech recognizer, a natural language translator (for converting a word sequence into a sequence of signs), and a 3D avatar animation module (for playing back the signs). The second module is a Spoken Spanish generator from sign writing composed of a visual interface (for specifying a sequence of signs), a language translator (for generating the sequence of words in Spanish), and finally, a text to speech converter. For language translation, the system integrates three technologies: an example based strategy, a rule based translation method and a statistical translator. This paper also includes a detailed description of the evaluation carried out in the Local Traffic Office in the city of Toledo (Spain) involving real government employees and deaf people. This evaluation includes objective measurements from the system and subjective information from questionnaire

Low-resource language recognition using a fusion of phoneme posteriorgram counts, acoustic and glottal-based i-vectors

This paper presents a description of our system for the Albayzin 2012 LRE competition. One of the main characteristics of this evaluation was the reduced number of available files for training the system, especially for the empty condition where no training data set was provided but only a development set. In addition, the whole database was created from online videos and around one third of the training data was labeled as noisy files. Our primary system was the fusion of three different i-vector based systems: one acoustic system based on MFCCs, a phonotactic system using trigrams of phone-posteriorgram counts, and another acoustic system based on RPLPs that improved robustness against noise. A contrastive system that included new features based on the glottal source was also presented. Official and postevaluation results for all the conditions using the proposed metrics for the evaluation and the Cavg metric are presented in the paper

Carbon stocks and changes in biomass of Mediterranean woody crops over a six-year period in NE Spain

Carbon sequestration and storage in biomass is one of the most important measures to mitigate climate change. Mediterranean woody crops can sequestrate carbon in the biomass of their permanent structures for decades; however, very few studies have focused on an assessment of biomass and carbon sequestration in these types of crops. This study is the first to estimate above- and belowground biomass carbon stock in Mediterranean woody crops through a bottom-up approach in the NE Iberian Peninsula in 2013. Moreover, this is the first time that an assessment of the annual changes in carbon stock in the study area over a six-year period is presented. For this purpose, eight crop- and site-specific equations relating biomass or biometric variables to crop age were calculated. Most of the data were our own measurements, but unpublished data supplied from other authors as well as data from literature were also considered. Census of Agriculture data was used to scale results from individual data up to the municipality level at the regional scale. Results show that in woody cropland in NE Spain the total biomass carbon stock in 2013 was 5.48 Tg C, with an average value of 16.44 ± 0.18 Mg C ha−1. Between 2013 and 2019, although there was a 2.8% mean annual decrease in the area covered by woody crops, the carbon stock in the biomass of these crops increased annually by 3.8% due to the growth of the remaining woody cropland. This new estimation of carbon stocks may contribute to better understand carbon balances and serve as a baseline to global inventories. It may also serve to assess and manage carbon storage as an ecosystem service provided by Mediterranean woody cropland for mitigating climate change and, in combination with adaptive strategies, for supporting a productive and resilient agro-food system.info:eu-repo/semantics/publishedVersio

n-gram Frequency Ranking with additional sources of information in a multiple-Gaussian classifier for Language Identification

We present new results of our n-gram frequency ranking used for language identification. We use a Parallel phone recognizer (as in PPRLM), but instead of the language model, we create a ranking with the most frequent n-grams. Then we compute the distance between the input sentence ranking and each language ranking, based on the difference in relative positions for each n-gram. The objective of this ranking is to model reliably a longer span than PPRLM. This approach overcomes PPRLM (15% relative improvement) due to the inclusion of 4-gram and 5-gram in the classifier. We will also see that the combination of this technique with other sources of information (feature vectors in our classifier) is also advantageous over PPRLM, showing also a detailed analysis of the relevance of these sources and a simple feature selection technique to cope with long feature vectors. The test database has been significantly increased using cross-fold validation, so comparisons are now more reliable