Machine Learning Model Development for Classification of Audio Commands

Kaveh Heidary

doi:10.32604/jai.2026.072857

January 1, 2026Journal on artificial intelligenceOpen Access

Machine Learning Model Development for Classification of Audio Commands

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Key Points

The aim is to develop and evaluate CNN models for classifying spoken words in limited vocabularies.
Developed convolutional neural network models
Evaluated models on audio data
Analyzed performance for classification accuracy
Achieved high accuracy in classifying limited vocabulary spoken commands
Demonstrated effectiveness of CNN models in audio command recognition

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Implication

This research investigates machine learning models for classifying audio commands in ASR systems, indicating their importance in voice technology.

Abstract

This paper presents a comprehensive investigation into the development and evaluation of Convolutional Neural Network (CNN) models for limited-vocabulary spoken word classification, a fundamental component of many voice-contr... | Find, read and cite all the research you need on Tech Science Press

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Cite This Study

Kaveh Heidary (2026) studied this question.

synapsesocial.com/papers/699fe36b95ddcd3a253e7345 https://doi.org/10.32604/jai.2026.072857

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Machine Learning Model Development for Classification of Audio Commands

Key Points

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Implication

Abstract

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Machine Learning Model Development for Classification of Audio Commands

Key Points

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Implication

Abstract

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