Saved in:
Bibliographic Details
Main Author: Ranga.Jaswanth, Ootla.Eswar Sai, G.Rajashekar, Ms. S.A.NEELAVANI
Format: Recurso digital
Language:
Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.19908040
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866901812377812992
author Ranga.Jaswanth, Ootla.Eswar Sai, G.Rajashekar, Ms. S.A.NEELAVANI
author_facet Ranga.Jaswanth, Ootla.Eswar Sai, G.Rajashekar, Ms. S.A.NEELAVANI
contents <h2>Abstract</h2> <div class="ijct-txt">This study describes the deployment of a voice-activated chatbot designed to assist expectant mothers by offering trustworthy maternal health information. To provide precise and contextually aware responses, the system employs a Retrieval-Augmented Generation (RAG) technique, which combines a language model with a local knowledge store. We developed this totally with free and open-source technologies to make the solution more accessible in rural or low-resource environments. Open-source approaches, such as Whisper for speech-to-text, are used to add voice capabilities. To ensure accuracy and validity, the data is also gathered from reputable sources like the WHO and other health portals. We used PDFs from these sources for RAG and stored them in vector databases for efficient document retrieval, as this system aims to bridge the information gap.</div> <h2>Keywords</h2> <div class="ijct-txt">Maternal health, RAG, chatbot, voice interface, NLP, vector database</div>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19908040
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle MATERNAL HEALTH BOT USING RAG ARCHITECTURE
Ranga.Jaswanth, Ootla.Eswar Sai, G.Rajashekar, Ms. S.A.NEELAVANI
<h2>Abstract</h2> <div class="ijct-txt">This study describes the deployment of a voice-activated chatbot designed to assist expectant mothers by offering trustworthy maternal health information. To provide precise and contextually aware responses, the system employs a Retrieval-Augmented Generation (RAG) technique, which combines a language model with a local knowledge store. We developed this totally with free and open-source technologies to make the solution more accessible in rural or low-resource environments. Open-source approaches, such as Whisper for speech-to-text, are used to add voice capabilities. To ensure accuracy and validity, the data is also gathered from reputable sources like the WHO and other health portals. We used PDFs from these sources for RAG and stored them in vector databases for efficient document retrieval, as this system aims to bridge the information gap.</div> <h2>Keywords</h2> <div class="ijct-txt">Maternal health, RAG, chatbot, voice interface, NLP, vector database</div>
title MATERNAL HEALTH BOT USING RAG ARCHITECTURE
url https://doi.org/10.5281/zenodo.19908040