The neural processing of masked speech: evidence for different mechanisms in the left and right temporal lobes

It has been previously demonstrated that extensive activation in the dorsolateral temporal lobes associated with masking a speech target with a speech masker, consistent with the hypothesis that competition for central auditory processes is an important factor in informational masking. Here, masking from speech and two additional maskers derived from the original speech were investigated. One of these is spectrally rotated speech, which is unintelligible and has a similar (inverted) spectrotemporal profile to speech. The authors also controlled for the possibility of "glimpsing" of the target signal during modulated masking sounds by using speech-modulated noise as a masker in a baseline condition. Functional imaging results reveal that masking speech with speech leads to bilateral superior temporal gyrus (STG) activation relative to a speech-in-noise baseline, while masking speech with spectrally rotated speech leads solely to right STG activation relative to the baseline. This result is discussed in terms of hemispheric asymmetries for speech perception, and interpreted as showing that masking effects can arise through two parallel neural systems, in the left and right temporal lobes. This has implications for the competition for resources caused by speech and rotated speech maskers, and may illuminate some of the mechanisms involved in informational masking.

Clustered functional MRI of overt speech production

To investigate the neural network of overt speech production, eventrelated fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speechrelated movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the corticaland subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum,reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.

Facilitating and disrupting speech perception in word deafness

Background: Word deafness is a rare condition where pathologically degraded speech perception results in impaired repetition and comprehension but otherwise intact linguistic skills. Although impaired linguistic systems in aphasias resulting from damage to the neural language system (here termed central impairments), have been consistently shown to be amenable to external influences such as linguistic or contextual information (e.g. cueing effects in naming), it is not known whether similar influences can be shown for aphasia arising from damage to a perceptual system (here termed peripheral impairments). Aims: This study aimed to investigate the extent to which pathologically degraded speech perception could be facilitated or disrupted by providing visual as well as auditory information. Methods and Procedures: In three word repetition tasks, the participant with word deafness (AB) repeated words under different conditions: words were repeated in the context of a pictorial or written target, a distractor (semantic, unrelated, rhyme or phonological neighbour) or a blank page (nothing). Accuracy and error types were analysed. Results: AB was impaired at repetition in the blank condition, confirming her degraded speech perception. Repetition was significantly facilitated when accompanied by a picture or written example of the word and significantly impaired by the presence of a written rhyme. Errors in the blank condition were primarily formal whereas errors in the rhyme condition were primarily miscues (saying the distractor word rather than the target). Conclusions: Cross-modal input can both facilitate and further disrupt repetition in word deafness. The cognitive mechanisms behind these findings are discussed. Both top-down influence from the lexical layer on perceptual processes as well as intra-lexical competition within the lexical layer may play a role. ���

A Unified Framework for e-Commerce Systems Development : Business Process Pattern Perspective

In electronic commerce, systems development is based on two fundamental types of models, business models and process models. A business model is concerned with value exchanges among business partners, while a process model focuses on operational and procedural aspects of business communication. Thus, a business model defines the what in an e-commerce system, while a process model defines the how. Business process design can be facilitated and improved by a method for systematically moving from a business model to a process model. Such a method would provide support for traceability, evaluation of design alternatives, and seamless transition from analysis to realization. This work proposes a unified framework that can be used as a basis to analyze, to interpret and to understand different concepts associated at different stages in e-Commerce system development. In this thesis, we illustrate how UN/CEFACT���s recommended metamodels for business and process design can be analyzed, extended and then integrated for the final solutions based on the proposed unified framework. Also, as an application of the framework, we demonstrate how process-modeling tasks can be facilitated in e-Commerce system design. The proposed methodology, called BP3 stands for Business Process Patterns Perspective. The BP3 methodology uses a question-answer interface to capture different business requirements from the designers. It is based on pre-defined process patterns, and the final solution is generated by applying the captured business requirements by means of a set of production rules to complete the inter-process communication among these patterns.

Speech Enhancement With Inventory Style Speech Resynthesis

We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted signal we are resynthesizing a new ���clean��� signal based on its likely characteristics. These characteristics are estimated from the distorted signal. A successful implementation of the proposed method is presented. Experiments were performed in a scenario with roughly one hour of clean speech training data. Our results show that the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments. Potential applications for the proposed method include jet cockpit communication systems and offline methods for the restoration of audio recordings.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

The Neural Substrates of Multisensory Speech Perception

Comprehending speech is one of the most important human behaviors, but we are only beginning to understand how the brain accomplishes this difficult task. One key to speech perception seems to be that the brain integrates the independent sources of information available in the auditory and visual modalities in a process known as multisensory integration. This allows speech perception to be accurate, even in environments in which one modality or the other is ambiguous in the context of noise. Previous electrophysiological and functional magnetic resonance imaging (fMRI) experiments have implicated the posterior superior temporal sulcus (STS) in auditory-visual integration of both speech and non-speech stimuli. While evidence from prior imaging studies have found increases in STS activity for audiovisual speech compared with unisensory auditory or visual speech, these studies do not provide a clear mechanism as to how the STS communicates with early sensory areas to integrate the two streams of information into a coherent audiovisual percept. Furthermore, it is currently unknown if the activity within the STS is directly correlated with strength of audiovisual perception. In order to better understand the cortical mechanisms that underlie audiovisual speech perception, we first studied the STS activity and connectivity during the perception of speech with auditory and visual components of varying intelligibility. By studying fMRI activity during these noisy audiovisual speech stimuli, we found that STS connectivity with auditory and visual cortical areas mirrored perception; when the information from one modality is unreliable and noisy, the STS interacts less with the cortex processing that modality and more with the cortex processing the reliable information. We next characterized the role of STS activity during a striking audiovisual speech illusion, the McGurk effect, to determine if activity within the STS predicts how strongly a person integrates auditory and visual speech information. Subjects with greater susceptibility to the McGurk effect exhibited stronger fMRI activation of the STS during perception of McGurk syllables, implying a direct correlation between strength of audiovisual integration of speech and activity within an the multisensory STS.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Improving Speech Interaction in Vehicles Using Context-Aware Information through A SCXML Framework

Speech Technologies can provide important benefits for the development of more usable and safe in-vehicle human-machine interactive systems (HMIs). However mainly due robustness issues, the use of spoken interaction can entail important distractions to the driver. In this challenging scenario, while speech technologies are evolving, further research is necessary to explore how they can be complemented with both other modalities (multimodality) and information from the increasing number of available sensors (context-awareness). The perceived quality of speech technologies can significantly be increased by implementing such policies, which simply try to make the best use of all the available resources; and the in vehicle scenario is an excellent test-bed for this kind of initiatives. In this contribution we propose an event-based HMI design framework which combines context modelling and multimodal interaction using a W3C XML language known as SCXML. SCXML provides a general process control mechanism that is being considered by W3C to improve both voice interaction (VoiceXML) and multimodal interaction (MMI). In our approach we try to anticipate and extend these initiatives presenting a flexible SCXML-based approach for the design of a wide range of multimodal context-aware HMI in-vehicle interfaces. The proposed framework for HMI design and specification has been implemented in an automotive OSGi service platform, and it is being used and tested in the Spanish research project MARTA for the development of several in-vehicle interactive applications.

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

In this paper, we describe a complete development platform that features different innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the different elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend database schema and contents, as well as cumulative information produced throughout the different steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the ���proposals��� that the platform dynamically provides at each step. In addition, the platform provides several other accelerations such as configurable templates that can be used to define the different tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the different tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend database. Additionally, the platform also allows the creation of speech grammars and prompts, database access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the different kind of methodologies followed to facilitate the design process at each one. Finally, we describe the results obtained in both a subjective and an objective evaluation with different designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%.

Contributions to the contextualization of human-machine spoken interaction systems

The design and development of spoken interaction systems has been a thoroughly studied research scope for the last decades. The aim is to obtain systems with the ability to interact with human agents with a high degree of naturalness and efficiency, allowing them to carry out the actions they desire using speech, as it is the most natural means of communication between humans. To achieve that degree of naturalness, it is not enough to endow systems with the ability to accurately understand the user���s utterances and to properly react to them, even considering the information provided by the user in his or her previous interactions. The system has also to be aware of the evolution of the conditions under which the interaction takes place, in order to act the most coherent way as possible at each moment. Consequently, one of the most important features of the system is that it has to be context-aware. This context awareness of the system can be reflected in the modification of the behaviour of the system taking into account the current situation of the interaction. For instance, the system should decide which action it has to carry out, or the way to perform it, depending on the user that requests it, on the way that the user addresses the system, on the characteristics of the environment in which the interaction takes place, and so on. In other words, the system has to adapt its behaviour to these evolving elements of the interaction. Moreover that adaptation has to be carried out, if possible, in such a way that the user: i) does not perceive that the system has to make any additional effort, or to devote interaction time to perform tasks other than carrying out the requested actions, and ii) does not have to provide the system with any additional information to carry out the adaptation, which could imply a lesser efficiency of the interaction, since users should devote several interactions only to allow the system to become adapted. In the state-of-the-art spoken dialogue systems, researchers have proposed several disparate strategies to adapt the elements of the system to different conditions of the interaction (such as the acoustic characteristics of a specific user���s speech, the actions previously requested, and so on). Nevertheless, to our knowledge there is not any consensus on the procedures to carry out these adaptation. The approaches are to an extent unrelated from one another, in the sense that each one considers different pieces of information, and the treatment of that information is different taking into account the adaptation carried out. In this regard, the main contributions of this Thesis are the following ones: Definition of a contextualization framework. We propose a unified approach that can cover any strategy to adapt the behaviour of a dialogue system to the conditions of the interaction (i.e. the context). In our theoretical definition of the contextualization framework we consider the system���s context as all the sources of variability present at any time of the interaction, either those ones related to the environment in which the interaction takes place, or to the human agent that addresses the system at each moment. Our proposal relies on three aspects that any contextualization approach should fulfill: plasticity (i.e. the system has to be able to modify its behaviour in the most proactive way taking into account the conditions under which the interaction takes place), adaptivity (i.e. the system has also to be able to consider the most appropriate sources of information at each moment, both environmental and user- and dialogue-dependent, to effectively adapt to the conditions aforementioned), and transparency (i.e. the system has to carry out the contextualizaton-related tasks in such a way that the user neither perceives them nor has to do any effort in providing the system with any information that it needs to perform that contextualization). Additionally, we could include a generality aspect to our proposed framework: the main features of the framework should be easy to adopt in any dialogue system, regardless of the solution proposed to manage the dialogue. Once we define the theoretical basis of our contextualization framework, we propose two cases of study on its application in a spoken dialogue system. We focus on two aspects of the interaction: the contextualization of the speech recognition models, and the incorporation of user-specific information into the dialogue flow. One of the modules of a dialogue system that is more prone to be contextualized is the speech recognition system. This module makes use of several models to emit a recognition hypothesis from the user���s speech signal. Generally speaking, a recognition system considers two types of models: an acoustic one (that models each of the phonemes that the recognition system has to consider) and a linguistic one (that models the sequences of words that make sense for the system). In this work we contextualize the language model of the recognition system in such a way that it takes into account the information provided by the user in both his or her current utterance and in the previous ones. These utterances convey information useful to help the system in the recognition of the next utterance. The contextualization approach that we propose consists of a dynamic adaptation of the language model that is used by the recognition system. We carry out this adaptation by means of a linear interpolation between several models. Instead of training the best interpolation weights, we make them dependent on the conditions of the dialogue. In our approach, the system itself will obtain these weights as a function of the reliability of the different elements of information available, such as the semantic concepts extracted from the user���s utterance, the actions that he or she wants to carry out, the information provided in the previous interactions, and so on. One of the aspects more frequently addressed in Human-Computer Interaction research is the inclusion of user specific characteristics into the information structures managed by the system. The idea is to take into account the features that make each user different from the others in order to offer to each particular user different services (or the same service, but in a different way). We could consider this approach as a user-dependent contextualization of the system. In our work we propose the definition of a user model that contains all the information of each user that could be potentially useful to the system at a given moment of the interaction. In particular we will analyze the actions that each user carries out throughout his or her interaction. The objective is to determine which of these actions become the preferences of that user. We represent the specific information of each user as a feature vector. Each of the characteristics that the system will take into account has a confidence score associated. With these elements, we propose a probabilistic definition of a user preference, as the action whose likelihood of being addressed by the user is greater than the one for the rest of actions. To include the user dependent information into the dialogue flow, we modify the information structures on which the dialogue manager relies to retrieve information that could be needed to solve the actions addressed by the user. Usage preferences become another source of contextual information that will be considered by the system towards a more efficient interaction (since the new information source will help to decrease the need of the system to ask users for additional information, thus reducing the number of turns needed to carry out a specific action). To test the benefits of the contextualization framework that we propose, we carry out an evaluation of the two strategies aforementioned. We gather several performance metrics, both objective and subjective, that allow us to compare the improvements of a contextualized system against the baseline one. We will also gather the user���s opinions as regards their perceptions on the behaviour of the system, and its degree of adaptation to the specific features of each interaction. Resumen El dise��o y el desarrollo de sistemas de interacci��n hablada ha sido objeto de profundo estudio durante las pasadas d��cadas. El prop��sito es la consecuci��n de sistemas con la capacidad de interactuar con agentes humanos con un alto grado de eficiencia y naturalidad. De esta manera, los usuarios pueden desempe��ar las tareas que deseen empleando la voz, que es el medio de comunicaci��n m��s natural para los humanos. A fin de alcanzar el grado de naturalidad deseado, no basta con dotar a los sistemas de la abilidad de comprender las intervenciones de los usuarios y reaccionar a ellas de manera apropiada (teniendo en consideraci��n, incluso, la informaci��n proporcionada en previas interacciones). Adicionalmente, el sistema ha de ser consciente de las condiciones bajo las cuales transcurre la interacci��n, as�� como de la evoluci��n de las mismas, de tal manera que pueda actuar de la manera m��s coherente en cada instante de la interacci��n. En consecuencia, una de las caracter��sticas primordiales del sistema es que debe ser sensible al contexto. Esta capacidad del sistema de conocer y emplear el contexto de la interacci��n puede verse reflejada en la modificaci��n de su comportamiento debida a las caracter��sticas actuales de la interacci��n. Por ejemplo, el sistema deber��a decidir cu��l es la acci��n m��s apropiada, o la mejor manera de llevarla a t��rmino, dependiendo del usuario que la solicita, del modo en el que lo hace, etc��tera. En otras palabras, el sistema ha de adaptar su comportamiento a tales elementos mutables (o din��micos) de la interacci��n. Dos caracter��sticas adicionales son requeridas a dicha adaptaci��n: i) el usuario no ha de percibir que el sistema dedica recursos (temporales o computacionales) a realizar tareas distintas a las que aqu��l le solicita, y ii) el usuario no ha de dedicar esfuerzo alguno a proporcionar al sistema informaci��n adicional para llevar a cabo la interacci��n. Esto ��ltimo implicar��a una menor eficiencia de la interacci��n, puesto que los usuarios deber��an dedicar parte de la misma a proporcionar informaci��n al sistema para su adaptaci��n, sin ning��n beneficio inmediato. En los sistemas de di��logo hablado propuestos en la literatura, se han propuesto diferentes estrategias para llevar a cabo la adaptaci��n de los elementos del sistema a las diferentes condiciones de la interacci��n (tales como las caracter��sticas ac��sticas del habla de un usuario particular, o a las acciones a las que se ha referido con anterioridad). Sin embargo, no existe una estrategia fija para proceder a dicha adaptaci��n, sino que las mismas no suelen guardar una relaci��n entre s��. En este sentido, cada una de ellas tiene en cuenta distintas fuentes de informaci��n, la cual es tratada de manera diferente en funci��n de las caracter��sticas de la adaptaci��n buscada. Teniendo en cuenta lo anterior, las contribuciones principales de esta Tesis son las siguientes: Definici��n de un marco de contextualizaci��n. Proponemos un criterio unificador que pueda cubrir cualquier estrategia de adaptaci��n del comportamiento de un sistema de di��logo a las condiciones de la interacci��n (esto es, el contexto de la misma). En nuestra definici��n te��rica del marco de contextualizaci��n consideramos el contexto del sistema como todas aquellas fuentes de variabilidad presentes en cualquier instante de la interacci��n, ya est��n relacionadas con el entorno en el que tiene lugar la interacci��n, ya dependan del agente humano que se dirige al sistema en cada momento. Nuestra propuesta se basa en tres aspectos que cualquier estrategia de contextualizaci��n deber��a cumplir: plasticidad (es decir, el sistema ha de ser capaz de modificar su comportamiento de la manera m��s proactiva posible, teniendo en cuenta las condiciones en las que tiene lugar la interacci��n), adaptabilidad (esto es, el sistema ha de ser capaz de considerar la informaci��n oportuna en cada instante, ya dependa del entorno o del usuario, de tal manera que adec��e su comportamiento de manera eficaz a las condiciones mencionadas), y transparencia (que implica que el sistema ha de desarrollar las tareas relacionadas con la contextualizaci��n de tal manera que el usuario no perciba la manera en que dichas tareas se llevan a cabo, ni tampoco deba proporcionar al sistema con informaci��n adicional alguna). De manera adicional, incluiremos en el marco propuesto el aspecto de la generalidad: las caracter��sticas del marco de contextualizaci��n han de ser portables a cualquier sistema de di��logo, con independencia de la soluci��n propuesta en los mismos para gestionar el di��logo. Una vez hemos definido las caracter��sticas de alto nivel de nuestro marco de contextualizaci��n, proponemos dos estrategias de aplicaci��n del mismo a un sistema de di��logo hablado. Nos centraremos en dos aspectos de la interacci��n a adaptar: los modelos empleados en el reconocimiento de habla, y la incorporaci��n de informaci��n espec��fica de cada usuario en el flujo de di��logo. Uno de los m��dulos de un sistema de di��logo m��s susceptible de ser contextualizado es el sistema de reconocimiento de habla. Este m��dulo hace uso de varios modelos para generar una hip��tesis de reconocimiento a partir de la se��al de habla. En general, un sistema de reconocimiento emplea dos tipos de modelos: uno ac��stico (que modela cada uno de los fonemas considerados por el reconocedor) y uno ling����stico (que modela las secuencias de palabras que tienen sentido desde el punto de vista de la interacci��n). En este trabajo contextualizamos el modelo ling����stico del reconocedor de habla, de tal manera que tenga en cuenta la informaci��n proporcionada por el usuario, tanto en su intervenci��n actual como en las previas. Estas intervenciones contienen informaci��n (sem��ntica y/o discursiva) que puede contribuir a un mejor reconocimiento de las subsiguientes intervenciones del usuario. La estrategia de contextualizaci��n propuesta consiste en una adaptaci��n din��mica del modelo de lenguaje empleado en el reconocedor de habla. Dicha adaptaci��n se lleva a cabo mediante una interpolaci��n lineal entre diferentes modelos. En lugar de entrenar los mejores pesos de interpolaci��n, proponemos hacer los mismos dependientes de las condiciones actuales de cada di��logo. El propio sistema obtendr�� estos pesos como funci��n de la disponibilidad y relevancia de las diferentes fuentes de informaci��n disponibles, tales como los conceptos sem��nticos extra��dos a partir de la intervenci��n del usuario, o las acciones que el mismo desea ejecutar. Uno de los aspectos m��s com��nmente analizados en la investigaci��n de la Interacci��n Persona-M��quina es la inclusi��n de las caracter��sticas espec��ficas de cada usuario en las estructuras de informaci��n empleadas por el sistema. El objetivo es tener en cuenta los aspectos que diferencian a cada usuario, de tal manera que el sistema pueda ofrecer a cada uno de ellos el servicio m��s apropiado (o un mismo servicio, pero de la manera m��s adecuada a cada usuario). Podemos considerar esta estrategia como una contextualizaci��n dependiente del usuario. En este trabajo proponemos la definici��n de un modelo de usuario que contenga toda la informaci��n relativa a cada usuario, que pueda ser potencialmente utilizada por el sistema en un momento determinado de la interacci��n. En particular, analizaremos aquellas acciones que cada usuario decide ejecutar a lo largo de sus di��logos con el sistema. Nuestro objetivo es determinar cu��les de dichas acciones se convierten en las preferencias de cada usuario. La informaci��n de cada usuario quedar�� representada mediante un vector de caracter��sticas, cada una de las cuales tendr�� asociado un valor de confianza. Con ambos elementos proponemos una definici��n probabil��stica de una preferencia de uso, como aquella acci��n cuya verosimilitud es mayor que la del resto de acciones solicitadas por el usuario. A fin de incluir la informaci��n dependiente de usuario en el flujo de di��logo, llevamos a cabo una modificaci��n de las estructuras de informaci��n en las que se apoya el gestor de di��logo para recuperar informaci��n necesaria para resolver ciertos di��logos. En dicha modificaci��n las preferencias de cada usuario pasar��n a ser una fuente adicional de informaci��n contextual, que ser�� tenida en cuenta por el sistema en aras de una interacci��n m��s eficiente (puesto que la nueva fuente de informaci��n contribuir�� a reducir la necesidad del sistema de solicitar al usuario informaci��n adicional, dando lugar en consecuencia a una reducci��n del n��mero de intervenciones necesarias para llevar a cabo una acci��n determinada). Para determinar los beneficios de las aplicaciones del marco de contextualizaci��n propuesto, llevamos a cabo una evaluaci��n de un sistema de di��logo que incluye las estrategias mencionadas. Hemos recogido diversas m��tricas, tanto objetivas como subjetivas, que nos permiten determinar las mejoras aportadas por un sistema contextualizado en comparaci��n con el sistema sin contextualizar. De igual manera, hemos recogido las opiniones de los participantes en la evaluaci��n acerca de su percepci��n del comportamiento del sistema, y de su capacidad de adaptaci��n a las condiciones concretas de cada interacci��n.

Design of an Advanced Platform for Citizen Participation Committed to Ensuring Freedom of Speech

This paper presents a proposal for an advanced system of debate in an environment of digital democracy which overcomes the limitations of existing systems. We have been especially careful in applying security procedures in telematic systems, for they are to offer citizens the guarantees that society demands. New functional tools have been included to ensure user authentication and to permit anonymous participation where the system is unable to disclose or even to know the identity of system users. The platform prevents participation by non-entitled persons who do not belong to the authorized group from giving their opinion. Furthermore, this proposal allows for verifying the proper function of the system, free of tampering or fraud intended to alter the conclusions or outcomes of participation. All these tools guarantee important aspects of both a social and technical nature, most importantly: freedom of expression, equality and auditability.