Search Results for author:
Found 22 papers, 5 papers with code
CIC NLP at SMM4H 2022: a BERT-based approach for classification of social media forum posts
This paper describes our submissions for the Social Media Mining for Health (SMM4H) 2022 shared tasks.
InkubaLM: A small language model for low-resource African languages
High-resource language models often fall short in the African context, where there is a critical need for models that are efficient, accessible, and locally relevant, even amidst significant computing and data constraints.
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual and textual data.
NLP Progress in Indigenous Latin American Languages
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements.
EthioMT: Parallel Corpus for Low-resource Ethiopian Languages
Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in high-resource languages.
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
We open-source our multilingual language models, new benchmark datasets for various downstream tasks, and task-specific fine-tuned language models and discuss the performance of the models.
Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets
We compile an Amharic instruction fine-tuning dataset and fine-tuned LLaMA-2-Amharic model.
First Attempt at Building Parallel Corpora for Machine Translation of Northeast India's Very Low-Resource Languages
This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India.
The Less the Merrier? Investigating Language Representation in Multilingual Models
Multilingual Language Models offer a way to incorporate multiple languages in one model and utilize cross-language transfer learning to improve performance for different Natural Language Processing (NLP) tasks.
AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR
To our knowledge, there is no publicly available research or benchmark on accented African clinical ASR, and speech data is non-existent for the majority of African accents.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Automatic Translation of Hate Speech to Non-hate Speech in Social Media Texts
In this paper, we investigate the issue of hate speech by presenting a novel task of translating hate speech into non-hate speech text while preserving its meaning.
AfriNames: Most ASR models "butcher" African Names
Useful conversational agents must accurately capture named entities to minimize error for downstream tasks, for example, asking a voice assistant to play a track from a certain artist, initiating navigation to a specific location, or documenting a laboratory result for a patient.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec
In this paper, we present a parallel Spanish-Mazatec and Spanish-Mixtec corpus for machine translation (MT) tasks, where Mazatec and Mixtec are two indigenous Mexican languages.
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models
This paper describes CIC NLP's submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas.
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users.
MasakhaNEWS: News Topic Classification for African languages
Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API).
Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages
For task B, we fine-tuned multilingual pre-trained language models that support many of the languages in the task.
Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages
In this work, we explore the applicability of low-compute approaches such as language adapters in the context of this low-resource double-bind.
Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities
This survey delves into the current state of natural language processing (NLP) for four Ethiopian languages: Amharic, Afaan Oromo, Tigrinya, and Wolaytta.
Transformer-based Model for Word Level Language Identification in Code-mixed Kannada-English Texts
Using code-mixed data in natural language processing (NLP) research currently gets a lot of attention.
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages
In this paper, we present AfroLM, a multilingual language model pretrained from scratch on 23 African languages (the largest effort to date) using our novel self-active learning framework.
The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation
Machine translation (MT) is one of the main tasks in natural language processing whose objective is to translate texts automatically from one natural language to another.
