Carlos Vaquero

E-inclusion technologies for the speech handicapped

This paper addresses the problem that disabled people face when accessing the new systems and technologies that are available nowadays. The use of speech technologies, specially helpful for motor handicapped people, becomes unapproachable when these people also suffer speech impairments, making the gap in the society wider for them. As a way to include speech impaired people in the technological society of today, two lines of work have been carried out. On one hand, a computer-aided speech therapy software has been developed for the speech training of children with different disabilities. This tool, available for free distribution, makes use of different state-of-the-art speech technologies to train different levels of the language. As a result of this work, the software is being used currently in several centers for special education with a very encouraging feedback about the capabilities of the system. On the other hand, research on the use of automatic speech recognition (ASR) systems for the speech impaired has been carried out. This work has focused on current techniques of speaker adaptation to know how these techniques, fruitfully used in other tasks, can deal with this specific kind of speech. The use of Maximum A Posterior (MAP) obtains an improvement of 60.61% compared to the results of a baseline speaker independent model.

Intra-session variability compensation and a hypothesis generation and selection strategy for speaker segmentation

This paper addresses the problem of speaker segmentation in two-speaker telephone conversations, using an eigenvoice based factor analysis approach. We present a set of improvements in the speaker segmentation system. First, we study two methods to compensate for intra-session variability, that is the variability present in a speaker during a single session. Secondly we propose a method to generate segmentation hypotheses that combined with a given confidence measure, enables the selection of correct hypotheses improving the overall segmentation performance. The proposed improvements are evaluated on the NIST Speaker Recognition Evaluation 2008 summed channel test condition, obtaining 28% relative improvement in terms of speaker segmentation error.

Analysis of acoustic features in speakers with cognitive disorders and speech impairments

This work presents the results in the analysis of the acoustic features (formants and the three suprasegmental features: tone, intensity and duration) of the vowel production in a group of 14 young speakers suffering different kinds of speech impairments due to physical and cognitive disorders. A corpus with unimpaired childrens speech is used to determine the reference values for these features in speakers without any kind of speech impairment within the same domain of the impaired speakers; this is 57 isolated words. The signal processing to extract the formant and pitch values is based on a Linear Prediction Coefficients (LPCs) analysis of the segments considered as vowels in a Hidden Markov Model (HMM) based Viterbi forced alignment. Intensity and duration are also based in the outcome of the automated segmentation. As main conclusion of the work, it is shown that intelligibility of the vowel production is lowered in impaired speakers even when the vowel is perceived as correct by human labelers. The decrease in intelligibility is due to a 30% of increase in confusability in the formants map, a reduction of 50% in the discriminative power in energy between stressed and unstressed vowels and to a 50% increase of the standard deviation in the length of the vowels. On the other hand, impaired speakers keep good control of tone in the production of stressed and unstressed vowels.

Speech Technology Applied to Children with Speech Disorders

This paper introduces an informatic applications for speech therapy in Spanish language based on the use of Speech Technology. The objective of this work is to help children with different speech impairments to improve their communication skills. Speech technology provides methods which can help children who suffer from speech disorders to develop pre-Language and Language. For pre-Language development the informatic application works on speech activity detection and intensity control, and for Language the application works on three levels of language: phonological, semantic and syntactic. This application is designed to enable those suffer from speech disorders to train their communication capabilities in an easy and entertaining way. This tool is available for free distribution.

Quality Assessment for Speaker Diarization and Its Application in Speaker Characterization

There are many applications related to speaker characterization, specially in telephone environments, where large datasets are available but not directly useful since there are two speakers involved in every recording. Even with very accurate speaker diarization systems, we can expect to find some recordings with low diarization accuracy. The use of these recordings may reduce the accuracy of any speaker characterization technology. Therefore, it is highly desirable to detect those recordings where the speakers are correctly segmented, in order to discard or process manually the remaining ones before feeding them into the application. In this work we propose a set of confidence measures to assess the quality of a hypothetical diarization output, in order to detect those recordings that are correctly segmented. We show that these confidence measures enable us to retrieve most of the desired recordings from a given dataset, discarding those recordings that degrade the overall accuracy of an application that make use of speaker characterization technologies.

Aplicación de las Tecnologías del Habla al Desarrollo del Prelenguaje y el Lenguaje

This paper shows a study on the use of Speech Technologies to help people with different speech impairments.