跨学科科学,造福人类的创新。第01卷/2026年9月
IJSTIR-ESNE · SEPTEMBER 2026

Linguo:基于人工智能和自然语言处理的智能移动应用开发,用于支持儿童言语、语言和沟通治疗

Abstract

The digital transformation of healthcare services has encouraged the development of technological solutions designed to support therapeutic processes, particularly in areas related to communication, learning, and child development. In this context, artificial intelligence (AI), natural language processing (NLP), and automatic speech recognition (ASR) offer opportunities to develop interactive tools that complement interventions conducted by speech-language therapy specialists. However, automated analysis of children's speech presents challenges associated with phonetic variability, linguistic development, acoustic conditions, data privacy, and the need for professional supervision.

The objective of this research is to propose the design and development of Linguo, an intelligent mobile application based on artificial intelligence and natural language processing, intended to support activities involving stimulation, practice, and monitoring of children's speech, language, and communication skills. The study adopts a technological, descriptive, and applied approach through the analysis of speech recognition tools, machine learning algorithms, audio signal processing, and adaptive interaction strategies.

The methodology includes the design of a modular architecture integrating an interactive mobile interface, linguistic activities, audio capture and processing, artificial intelligence models, secure data storage, and a professional monitoring module. Evaluation indicators are established to assess speech recognition accuracy, usability, accessibility, performance, data protection, and the alignment of activities with therapeutic objectives.

The findings of the technological analysis identify the functional components of the application, appropriate technologies for implementation, and criteria for future technical and clinical validation. The study concludes that Linguo represents a technological innovation proposal with the potential to complement pediatric speech-language therapy, support continuity of supervised activities, and facilitate structured progress monitoring without replacing professional assessment or intervention.

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