<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>The paper shows the understanding of a topic recognition problem like the speech recognition system based on Natural Language Processing (NLP) and the steps of its implementation of a rules-based approach, which is able to classify given audio materials based on predefined topics in real-time. During implementation, a statistical vocabulary was developed. Google Speech API (<italic>Application Programming Interface</italic>) was employed for subtitling audio materials, and the most ideal time frame for reception was identified through several experiments. The motivation of this work is based on the deficiency of similar simple systems for Hungarian topic recognition, even though numerous international languages already utilize multiple Automatic Sound Recognition (ASR) systems.</p>
</abstract>

The paper shows the understanding of a topic recognition problem like the speech recognition system based on Natural Language Processing (NLP) and the steps of its implementation of a rules-based approach, which is able to classify given audio materials based on predefined topics in real-time. During implementation, a statistical vocabulary was developed. Google Speech API (Application Programming Interface) was employed for subtitling audio materials, and the most ideal time frame for reception was identified through several experiments. The motivation of this work is based on the deficiency of similar simple systems for Hungarian topic recognition, even though numerous international languages already utilize multiple Automatic Sound Recognition (ASR) systems.

Topic Identification in Voice Recordings 

Acta Marisiensis. Seria Technologica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Topic Identification in Voice Recordings"}

The paper shows the understanding of a topic recognition problem like the speech recognition system based on Natural Language Processing (NLP) and the steps of...

Topic Identification in Voice Recordings

Publié en ligne: 14 déc. 2023

Pages: 43 - 48

DOI: https://doi.org/10.2478/amset-2023-0017

Mots clés
speech recognition, statistics for performance analysis, natural language processing, machine learning, prediction in healthcare

© 2023 Zsuzsa Simo, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Topic Identification in Voice Recordings

Publié en ligne: 14 déc. 2023

Pages: 43 - 48

DOI: https://doi.org/10.2478/amset-2023-0017

Mots clésspeech recognition, statistics for performance analysis, natural language processing, machine learning, prediction in healthcare

© 2023 Zsuzsa Simo, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
speech recognition, statistics for performance analysis, natural language processing, machine learning, prediction in healthcare