SofiaFala: Software Inteligente de Apoio à Fala

  • Pedro Henrique D’Almeida Giberti Rissato USP
  • Alessandra Alaniz Macedo USP

Resumo


Approximately 2.7 million Brazilians may have some speech disorder, according to the Brazilians Institute of Geography and Statistics. Language therapies usually employ speech exercises at home for people with speech disorders without close specialized supervision. There are fundamental movements. Assistive technology and machine learning can support the development of speech pronunciation practice systems. SofiaFala is a mobile application that supports prescription, monitoring, execution, and evaluation of speech therapies. It also supports speech therapist data analysis for the outside clinical environment. In the two last years, 1,400 speech therapists have required access to the SofiaFala.

Palavras-chave: Speech & Pattern Recognition, Machine Learning, Speech Disorder

Referências

CRF de Andrade, Débora Maria Befi-Lopes, Fernanda Dreux Miranda Fernandes, and Haydée Fiszbein Wertzner. 2004. ABFW: teste de linguagem infantil nas áreas de fonologia, vocabulário, fluência e pragmática. São Paulo: Pró-Fono (2004).

T. M. M. F. BARBOSA, G. R. G. RABELO, I. L. B. LIMA, and I. C. DELGADO. 2015. Avaliação da linguagem na Síndrome de Down: análise de protocolos desenvolvidos em extensão universitária. In XXIII CONGRESSO BRASILEIRO DE FONOAUDIOLOGIA . 6119.

Cláudia Maria de Felício, Gislaine Aparecida Folha, Alice Stahl Gaido, Márcio de Mendonça Mancine Dantas, and Paulo Mazzoncini de Azevedo-Marques. 2014. Computerized protocol of orofacial myofunctional evaluation with scores: usability and validity. CoDAS 26, 4 (July 2014), 322–327. https://doi.org/10.1590/2317-1782/201420140021

Vanessa Giacchini, Aline Tonial, and Helena Mota. 2013. Aspectos de linguagem e motricidade oral observados em crianças atendidas em um setor de estimulação precoce. Distúrbios da Comunicação 25, 2 (2013). https://revistas.pucsp.br/dic/article/view/16478

Fernando Meloni, Bianca Sicchieri, Patricia Mandrá, Renato Bulcão-Neto, and Alessandra Alaniz Macedo. 2021. A Nonverbal Recognition Method to Assist Speech. In 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) . 360–365. https://doi.org/10.1109/CBMS52027.2021.00111

David Patterson. 2009. Molecular genetic analysis of Down syndrome. Human Genetics 126, 1 (01 Jul 2009), 195–214. https://doi.org/10.1007/s00439-009-0696-8

Mike Potel. 1996. MVP: Model-View-Presenter the Taligent programming model for C++ and Java. Taligent Inc (1996), 20.

Francisco Carlos M. Souza, Alinne C. Correa Souza, Carolina Y. V. Watanabe, Patricia Pupin Mandrá, and Alessandra Alaniz Macedo. 2019. An Analysis of Visual Speech Features for Recognition of Non-articulatory Sounds using Machine Learning. International Journal of Computer Applications 177, 16 (Nov 2019), 1–9. https://doi.org/10.5120/ijca2019919393

Michael Stonebraker. 2010. SQL Databases v. NoSQL Databases. Commun. ACM 53, 4 (April 2010), 10–11. https://doi.org/10.1145/1721654.1721659

D. L. ZAURA. 2018. Perfil de usuários atendidos em serviço de diagnóstico de linguagem de média complexidade. Trabalho de Conclusão de Curso.
Publicado
05/11/2021
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RISSATO, Pedro Henrique D’Almeida Giberti; MACEDO, Alessandra Alaniz. SofiaFala: Software Inteligente de Apoio à Fala. In: WORKSHOP DE FERRAMENTAS E APLICAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 27. , 2021, Minas Gerais. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 91-94. ISSN 2596-1683. DOI: https://doi.org/10.5753/webmedia_estendido.2021.17620.