Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

A Deep Learning Approach for Yoruba Language Next Word Generation

Créateur:
Edn
Éditeur:
IEEE
Hôte:

Visit

doi.org

Tasks

language modeling

Languages

Yoruba

Licenses

https://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-037

Similaires

Word Sequence Prediction Model for the Tigrigna Language Using a Deep Learning Approachbekykm/ADBiLSTM-for-Afaan-Oromo-Next-Word-GenerationA Yoruba Language Automatic Speech Recognition System using Deep Learning ApproachWord-level Afan Oromo Sign Language Recognition Using Deep Learning ApproachDeep Learning Shape Trajectories for Isolated Word Sign Language RecognitionAttention-Driven Bidirectional LSTM Neural Network for Afaan Oromo Next Word Generation

Word Sequence Prediction Model for the Tigrigna Language Using a Deep Learning Approach

This research explores the development of a word sequence prediction model for the Tigrigna language

bekykm/ADBiLSTM-for-Afaan-Oromo-Next-Word-Generation

This repository provides a resource for neural network designed for next word generation in the Afaa

A Yoruba Language Automatic Speech Recognition System using Deep Learning Approach

Word-level Afan Oromo Sign Language Recognition Using Deep Learning Approach

Abstract S ign language is a primary commun

Deep Learning Shape Trajectories for Isolated Word Sign Language Recognition

In this paper, we propose an efficient trajectories analysis solution for the recognition of Isolate

Attention-Driven Bidirectional LSTM Neural Network for Afaan Oromo Next Word Generation

Effective communication through digital platforms often faces issues like misspellings and inefficie