Repository logo
 
Loading...
Profile Picture
Person

Ascensão, Mariana

Search Results

Now showing 1 - 2 of 2
  • The BioVisualSpeech corpus of words with sibilants for speech therapy games development
    Publication . Cavaco, Sofia; Guimarães, Isabel; Ascensão, Mariana; Abad, Alberto; Anjos, Ivo; Oliveira, Francisco; Martins, Sofia; Marques, Nuno; Eskenazi, Maxine; Magalhães, João; Grilo, Ana Margarida
    Abstract: In order to develop computer tools for speech therapy that reliably classify speech productions, there is a need for speech production corpora that characterize the target population in terms of age, gender, and native language. Apart from including correct speech productions, in order to characterize the target population, the corpora should also include samples from people with speech sound disorders. In addition, the annotation of the data should include information on the correctness of the speech productions. Following these criteria, we collected a corpus that can be used to develop computer tools for speech and language therapy of Portuguese children with sigmatism. The proposed corpus contains European Portuguese children’s word productions in which the words have sibilant consonants. The corpus has productions from 356 children from 5 to 9 years of age. Some important characteristics of this corpus, that are relevant to speech and language therapy and computer science research, are that (1) the corpus includes data from children with speech sound disorders; and (2) the productions were annotated according to the criteria of speech and language pathologists, and have information about the speech production errors. These are relevant features for the development and assessment of speech processing tools for speech therapy of Portuguese children. In addition, as an illustration on how to use the corpus, we present three speech therapy games that use a convolutional neural network sibilants classifier trained with data from this corpus and a word recognition module trained on additional children data and calibrated and evaluated with the collected corpus.
  • A serious mobile game with visual feedback for training sibilant consonants
    Publication . Anjos, Ivo; Grilo, Ana Margarida; Ascensão, Mariana; Guimarães, Isabel; Magalhães, João; Cavaco, Sofia
    Abstract. The distortion of sibilant sounds is a common type of speech sound disorder (SSD) in Portuguese speaking children. Speech and language pathologists (SLP) frequently use the isolated sibilants exercise to assess and treat this type of speech errors. While technological solutions like serious games can help SLPs to motivate the children on doing the exercises repeatedly, there is a lack of such games for this specic exercise. Another important aspect is that given the usual small number of therapy sessions per week, children are not improving at their maximum rate, which is only achieved by more intensive therapy. We propose a serious game for mobile platforms that allows children to practice their isolated sibilants exercises at home to correct sibilant distortions. This will allow children to practice their exercises more frequently, which can lead to faster improvements. The game, which uses an automatic speech recognition (ASR) system to classify the child sibilant productions, is controlled by the child's voice in real time and gives immediate visual feedback to the child about her sibilant productions. In order to keep the computation on the mobile platform as simple as possible, the game has a client-server architecture, in which the external server runs the ASR system. We trained it using raw Mel frequency cepstral coe cients, and we achieved very good results with an accuracy test score of above 91% using support vector machines.