Contributions to keyword spotting and spoken term: detection for information retrieval in audio minig

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, marzo de 200

Distributed Spanish Sign Language synthesizer architectures

This is an electronic version of the paper presented at the Congreso Internacional de Interacción Persona-Ordenador, held in Bercelona on 2009This work presents the design of a distributed Sign Language synthesis architecture. The main objective of this design is to adapt the synthesis process to the diversity of the user devices. The synthesis process has been divided into several independent modules that can be executed either in a synthesis server or in the client device. Depending on the modules assigned to the server or the client, four different scenarios have been defined. These scenarios may vary from a heavy client design which executes the whole synthesis, to a light client design similar to a video player. These four scenarios will provide the maximum signed message quality independently of the device hardware resource

Integration of a talking head into a Spanish Sign Language synthesizer

This is an electronic version of the paper presented at the Congreso Internacional de Interacción Persona-Ordenador, held in Bercelona on 2009In this paper, we present an integration of a talking head within a Spanish Sign Language synthesizer. The whole system consists of three different steps: First, the input acoustic signal is transformed into a sequence of phones by means of a speech recognition process. This sequence of phones is mapped in a second step to a sequence of visemes and finally, the resulting sequence of visemes is played by means of a talking head integrated into the avatar used in the Spanish Sign Language synthesizer

An on-line system adding subtitles and sign language to Spanish audio-visual content

Deaf people cannot properly access the speech information stored in any kind of recording format (audio, video, etc). We present a system that provides with subtitling and Spanish Sign Language representation capabilities to allow Spanish Deaf population can access to such speech content. The system is composed by a speech recognition module, a machine translation module from Spanish to Spanish Sign Language and a Spanish Sign Language synthesis module. On the deaf person side, a user-friendly interface with subtitle and avatar components allows him/her to access the speech information

A rule-based translation from written Spanish to Spanish Sign Language glosses

This is the author’s version of a work that was accepted for publication in Computer Speech and Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Speech and Language, 28, 3 (2015) DOI: 10.1016/j.csl.2013.10.003One of the aims of Assistive Technologies is to help people with disabilities to communicate with others and to provide means of access to information. As an aid to Deaf people, we present in this work a production-quality rule-based machine system for translating from Spanish to Spanish Sign Language (LSE) glosses, which is a necessary precursor to building a full machine translation system that eventually produces animation output. The system implements a transfer-based architecture from the syntactic functions of dependency analyses. A sketch of LSE is also presented. Several topics regarding translation to sign languages are addressed: the lexical gap, the bootstrapping of a bilingual lexicon, the generation of word order for topic-oriented languages, and the treatment of classifier predicates and classifier names. The system has been evaluated with an open-domain testbed, reporting a 0.30 BLEU (BiLingual Evaluation Understudy) and 42% TER (Translation Error Rate). These results show consistent improvements over a statistical machine translation baseline, and some improvements over the same system preserving the word order in the source sentence. Finally, the linguistic analysis of errors has identified some differences due to a certain degree of structural variation in LSE

Intérprete de lenguaje de signos en español multidispositivo

Versión electrónica de la ponencia presentada en Conferencia Ibero-Americana IADIS WWW/Internet 2006, celebrado en Murcia en 2006En este artículo presentamos un transcriptor de texto a lenguaje de signos distribuido y multidispositivo. La presentación al usuario final del lenguaje de signos es realizada por un personaje animado en tres dimensiones. Este transcriptor está creado para adaptar su salida a la capacidad de proceso del dispositivo receptor. Por lo que puede ser utilizado por un usuario en un ordenador personal para transcribir una página Web, o en un teléfono móvil para transcribir una conversación (utilizando un reconocedor de voz). La flexibilidad del sistema permite adaptarlo a varios idiomas o usarlo como un simple elemento para mejorar una interfaz multimedia

An evolutionary confidence measure for spotting words in speech recognition

Proceedings of 8th International Conference on Practical Applications of Agents and Multiagent Systems, held in Salamanca (Spain), on April 26-28, 2010The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-12433-4_50Confidence measures play a very important role in keyword spotting systems. Traditional confidence measures are based on the score computed when the audio is decoded. Classification-based techniques by means of Multi-layer Perceptrons (MLPs) and Support Vector Machines have shown to be powerful ways to improve the final performance in terms of hits and false alarms. In this work we evaluate a keyword spotting system performance by incorporating an evolutionary algorithm as confidence measure and compare its performance with traditional classification techniques based on MLP. We show that this evolutionary algorithm gets better performance than the MLP when False Alarm (FA) is high and always performs better than the confidence measure based on the single score computed during the audio decoding.The authors acknowledge support from the Spanish Ministerio de Ciencia e innovacin, project TIN2007-66862-C02-02, and from CAM/UAM, project number CCG08-UAM/TIC-4428

A Contextual GMM-HMM Smart Fiber Optic Surveillance System for Pipeline Integrity Threat Detection

This paper presents a novel pipeline integrity surveillance system aimed to the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry ( $\phi$ -OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level in a Gaussian Mixture Model-Hidden Markov Model (GMM-HMM)-based pattern classification system and applies a system combination strategy for acoustic trace decision. System combination relies on majority voting of the decisions given by the individual contextual information sources and the number of states used for HMM modelling. The system runs in two different modes: (1) machine+activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed to detect threats no matter what the real activity being conducted is. In comparison with the previous systems based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information and the GMM-HMM approach improves the results for both machine+activity identification (7.6% of relative improvement with respect to the best published result in the literature on this task) and threat detection (26.6% of relative improvement in the false alarm rate with 2.1% relative reduction in the threat detection rate).European CommissionMinisterio de Economía y CompetitividadComunidad de Madri

Emotional adaptive training for speaker verification

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Bie, F., Wang, D., Zheng, T.F., Tejedor, J., Chen, R. "Emotional adaptive training for speaker verification", in Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific, 2013, pp. 1-4Speaker verification suffers from significant performance degradation with emotion variation. In a previous study, we have demonstrated that an adaptation approach based on MLLR/CMLLR can provide a significant performance improvement for verification on emotional speech. This paper follows this direction and presents an emotional adaptive training (EAT) approach. This approach iteratively estimates the emotion-dependent CMLLR transformations and re-trains the speaker models with the transformed speech, which therefore can make use of emotional enrollment speech to train a stronger speaker model. This is similar to the speaker adaptive training (SAT) in speech recognition. The experiments are conducted on an emotional speech database which involves speech recordings of 30 speakers in 5 emotions. The results demonstrate that the EAT approach provides significant performance improvements over the baseline system where the neutral enrollment data are used to train the speaker models and the emotional test utterances are verified directly. The EAT also outperforms another two emotionadaptation approaches in a significant way: (1) the CMLLR-based approach where the speaker models are trained with the neutral enrollment speech and the emotional test utterances are transformed by CMLLR in verification; (2) the MAP-based approach where the emotional enrollment data are used to train emotion-dependent speaker models and the emotional utterances are verified based on the emotion-matched models.This work was supported by the National Natural Science Foundation of China under Grant No. 61271389 and the National Basic Research Program (973 Program) of China under Grant No. 2013CB329302

Interactive Web platform for encouraging reader comprehension

This is an electronic version of the paper presented at the IADIS International Conference WWW/Internet 2003, ICWI 2003, held in Algarve on 2003This paper shows a web tool designed to encourage an active reader comprehension. Being a web-technology based system, it allows easy access for a wide number of users around the world, while at the same time it is easy to update. The system may be used by teachers who create exercises, “validators” who check them before being published and students who can complete these exercises at school or at home. Many of the classical grammar and vocabulary exercises will be seen now by the students as a game, in a similar way to crosswords. Moreover instant answers will be provided. This tool allows teachers not only to create interactive and guided reading exercises, but also to perform statistic follow-ups and global evaluations over a great population of readers. Feed-back has been preponderated so as to give the students the possibility to auto-evaluate their progress