Automat Parsing of Audio Recordings. Testing Children with Dyslalia. Theoretical Background

TL;DR

This paper introduces an automated method for parsing audio recordings of children with dyslalia, utilizing the ADM algorithm and specialized audio processing techniques to improve speech problem identification.

Contribution

The paper presents the ADM algorithm and a novel marker placement method for accurate parsing of audio recordings from children with speech disorders.

Findings

Developed the ADM algorithm for audio parsing.

Analyzed the complexity of the proposed solution.

Created a C# software toolkit for audio stream handling.

Abstract

In this paper we present our researches regarding automat parsing of audio recordings. These recordings are obtained from children with dyslalia and are necessary for an accurate identification of speech problems. We develop the ADM algorithm and we analyze the complexity of this solution. We utilize a digital voice recorder in High Quality mode and with VCVA (Variable Control Voice Actuator) activated. The record format is IMA-ADPCM, 16KHz and 4bits (16 bits PCM). A microphone was placed at 10 cm from mouth in order to minimize environment noise. A software set of classes (C#) was created for handling audio stream (read, conversion between different format, write). We also propose an original solution for placing markers in audio stream. These markers are needed for a correct parsing af full recoding.