The BioVisualSpeech European Portuguese Sibilants Corpus

Grilo, Margarida; Guimarães, Isabel; Ascensão, Mariana; Abad, Alberto; Anjos, Ivo; Magalhães, João; Cavaco, Sofia

doi:10.1007/978-3-030-41505-1_3

Cited by 3 publications

(2 citation statements)

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“…Section 4.2 describes in more detail the set of words and the protocol used to record the sibilant word productions. While here we focus on the words with sibilants data set, for more details on the isolated sibilants see Reference [11].…”

Section: The Corpus Of Words With Sibilantsmentioning

confidence: 99%

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The BioVisualSpeech Corpus of Words with Sibilants for Speech Therapy Games Development

et al. 2020

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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 developmentand assessment of speech processing toolsfor 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.

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Section: The Corpus Of Words With Sibilantsmentioning

confidence: 99%

“…In order to develop the automatic speech processing modules for our serious games for sigmatism, we built a corpus of children's speech that was previously proposed in Reference [11]. This corpus contains isolated sibilants productions and productions of words with sibilants.…”

Section: Introductionmentioning

confidence: 99%

The BioVisualSpeech Corpus of Words with Sibilants for Speech Therapy Games Development

et al. 2020

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A Longitudinal Evaluation of Tablet-Based Child Speech Therapy with Apraxia World

Hair

Ballard

Markoulli

et al. 2021

ACM Trans. Access. Comput.

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Digital games can make speech therapy exercises more enjoyable for children and increase their motivation during therapy. However, many such games developed to date have not been designed for long-term use. To address this issue, we developed Apraxia World, a speech therapy game specifically intended to be played over extended periods. In this study, we examined pronunciation improvements, child engagement over time, and caregiver and automated pronunciation evaluation accuracy while using our game over a multi-month period. Ten children played Apraxia World at home during two counterbalanced 4-week treatment blocks separated by a 2-week break. In one treatment phase, children received pronunciation feedback from caregivers and in the other treatment phase, utterances were evaluated with an automated framework built into the game. We found that children made therapeutically significant speech improvements while using Apraxia World, and that the game successfully increased engagement during speech therapy practice. Additionally, in offline mispronunciation detection tests, our automated pronunciation evaluation framework outperformed a traditional method based on goodness of pronunciation scoring. Our results suggest that this type of speech therapy game is a valid complement to traditional home practice.

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Detection of Voicing and Place of Articulation of Fricatives with Deep Learning in a Virtual Speech and Language Therapy Tutor

Anjos¹,

Eskénazi²,

Marques³

et al. 2020

Interspeech 2020

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Children with fricative distortion errors have to learn how to correctly use the vocal folds, and which place of articulation to use in order to correctly produce the different fricatives. Here we propose a virtual tutor for fricatives distortion correction. This is a virtual tutor for speech and language therapy that helps children understand their fricative production errors and how to correctly use their speech organs. The virtual tutor uses log Mel filter banks and deep learning techniques with spectral-temporal convolutions of the data to classify the fricatives in children's speech by place of articulation and voicing. It achieves an accuracy of 90.40% for place of articulation and 90.93% for voicing with children's speech. Furthermore, this paper discusses a multidimensional advanced data analysis of the first layer convolutional kernel filters that validates the usefulness of performing the convolution on the log Mel filter bank.

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The BioVisualSpeech European Portuguese Sibilants Corpus

Cited by 3 publications

References 11 publications

The BioVisualSpeech Corpus of Words with Sibilants for Speech Therapy Games Development

The BioVisualSpeech Corpus of Words with Sibilants for Speech Therapy Games Development

A Longitudinal Evaluation of Tablet-Based Child Speech Therapy with Apraxia World

Detection of Voicing and Place of Articulation of Fricatives with Deep Learning in a Virtual Speech and Language Therapy Tutor

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