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Browsing by Author "Sefara, Tshephisho J"

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Automatic speaker recognition system based on machine learning algorithms

Author: Mokgonyane, TB ; Sefara, Tshephisho J ; Modipa, Thipe I ; Mogale, MM ; Manamela, MJ ; Manamela, PJ Date: Jan 2019 Speaker recognition is a technique used to automatically recognize a speaker from a recording of their voice or speech utterance. Speaker recognition technology has improved over recent years and has become inexpensive and and reliable method ... Read more
Automatic speaker recognition system based on optimised machine learning algorithms

Author: Mokgonyane, TB ; Sefara, Tshephisho J ; Modipa, TI ; Manamela, MJ Date: Sep 2019 Speaker recognition is a technique that automatically identifies a speaker from a recording of their voice. Speaker recognition technologies are taking a new trend due to the progress in artificial intelligence and machine learning and have ... Read more
Classification of exaggerated news headlines

Author: Rangata, Mapitsi R ; Sefara, Tshephisho J Date: Feb 2024 The amount of data online is increasing as companies generate news articles daily. These news articles contain headlines that have a level of exaggeration aimed to win the readers. In addition, these companies are competing against one another; ... Read more
A cross-platform interface for automatic speaker identification and verification

Author: Mokgonyane, TB ; Sefara, Tshephisho J ; Manamela, MJ ; Modipa, TI Date: Aug 2021 The task of automatically identifying and/or verifying the identity of a speaker from a recording of a speech sample, known as automatic speaker recognition, has been studied for many years and automatic speaker recognition technologies have ... Read more
Digital forensics supported by machine learning for the detection of online sexual predatory chats

Author: Ngejane, Hombakazi C ; Eloff, JHP ; Sefara, Tshephisho J ; Marivate, VN Date: Mar 2021 Chat-logs are informative digital footprints available on Social Media Platforms (SMPs). With the rise of cybercrimes targeting children, chat-logs can be used to discover and flag harmful behaviour for the attention of law enforcement units. ... Read more
The effects of acoustic features of speech for automatic speaker recognition

Author: Mokgonyane, TB ; Sefara, Tshephisho J ; Manamela, MJ ; Modipa, TI ; Masekwameng, MS Date: Aug 2020 Automatic speaker recognition is the task of automatically determining or verifying the identity of a speaker from a recording of his or her speech sample and has been studied for many decades. One of the most important steps of speaker ... Read more
The effects of data size on text-independent automatic speaker identification system

Author: Mokgonyane, TB ; Sefara, Tshephisho J ; Manamela, MJ ; Modipa, TI Date: Aug 2019 Speaker recognition is a technique that automatically identifies a speaker from a recording of their speech utterance. Speaker recognition technologies are taking a new direction due to rapid progress in artificial intelligence. Research in ... Read more
The effects of normalisation methods on speech emotion recognition

Author: Sefara, Tshephisho J Date: Nov 2019 Speech emotion recognition systems require features to be extracted from the speech signal. These features include Time, Frequency, and Cepstral-domain features. To normalise features, it is a challenging task to select an appropriate ... Read more
Emotional speaker recognition based on machine and deep learning

Author: Sefara, Tshephisho J ; Mokgonyane, TB Date: Nov 2020 Speaker recognition is a method which recognise a speaker from characteristics of a voice. Speaker recognition technologies have been widely used in many domains. Most speaker recognition systems have been trained on normal clean recordings, ... Read more
Gender identification in Sepedi speech corpus

Author: Sefara, Tshephisho J ; Mokgonyane, TB Date: Aug 2021 Gender identification is the task of identifying the gender of the speaker from the audio signal. Most gender identification systems are developed using datasets belonging to well-resourced languages. There has been little focus on creating ... Read more
Grammar-driven text-to-speech application for articulation of mathematical expressions

Author: Mogale, MM ; Sefara, Tshephisho J ; Mokgonyane, TB Date: Sep 2020 Natural Language Processing (NLP) forms one of the important and fundamental components of speech synthesis while a language grammar forms one of the important requirements for NLP tasks. One of the major requirements in processing speech ... Read more
HMM-based speech synthesis system incorporated with language identification for low-resourced languages

Author: Sefara, Tshephisho J ; Mokgonyane, TB ; Manamela, MJ ; Modipa, TI Date: Aug 2019 Text-to-speech (TTS) synthesis systems are of benefit towards learning new or foreign languages. These systems are currently available for various major languages but not available for low-resourced languages. Scarcity of these systems may ... Read more
Improving short text classification through global augmentation methods

Author: Marivate, V ; Sefara, Tshephisho J Date: Aug 2020 We study the effect of different approaches to text augmentation. To do this we use three datasets that include social media and formal text in the form of news articles. Our goal is to provide insights for practitioners and researchers on ... Read more
Investigating an approach for low resource language dataset creation, curation and classification: Setswana and Sepedi

Author: Marivate, Vukosi N ; Sefara, Tshephisho J ; Chabalala, V ; Makhaya, K ; Mokgonyane, T ; Mokoena, R ; Modupe, A Date: May 2020 The recent advances in Natural Language Processing have only been a boon for well represented languages, negating research in lesser known global languages. This is in part due to the availability of curated data and research resources. One ... Read more
A natural language processing technique to identify exaggerated news titles

Author: Sefara, Tshephisho J ; Rangata, Mapitsi R Date: Oct 2023 Exaggerated news titles are used to deceive news readers and spread misleading information. This paper presents a new natural language processing (NLP) technique that identifies exaggerated news titles. The technique uses Jaccard similarity ... Read more
Practical approach on implementation of Wordnets for South African languages

Author: Sefara, Tshephisho J ; Mokgonyane, TB Date: Mar 2021 This paper proposes the implementation of WordNets for five South African languages, namely, Sepedi, Setswana, Tshivenda, isiZulu and isiXhosa to be added to open multilingual WordNets (OMW) on natural language toolkit (NLTK). The African ... Read more
A toolkit for text extraction and analysis for natural language processing tasks

Author: Sefara, Tshephisho J ; Mbooi, Mahlatse S ; Mashile, Katlego J ; Rambuda, Thompho ; Rangata, Mapitsi R Date: Aug 2022 Text extraction is an important part of natural language processing (NLP) tasks. Most NLP tasks like text classification, machine translation, text-to-speech, text-based language identification, text summarization, and named-entity recognition ... Read more
Topic classification of tweets in the broadcasting domain using machine learning methods

Author: Sefara, Tshephisho J ; Rangata, Mapitsi R Date: Aug 2023 Twitter is one of the microblogging sites with millions of daily users. Broadcast companies use Twitter to share short messages to engage or share opinions about a particular topic or product. With a large number of conversations available ... Read more
Training cross-lingual embeddings for Setswana and Sepedi

Author: Makgatho, M ; Marivate, V ; Sefara, Tshephisho J ; Wagner, V Date: Feb 2022 How can we transfer semantic information between two low-resourced African languages? With one language having more resources than the other? The problem is that African languages still lag in the advances of Natural Language Processing ... Read more
Transformer-based machine translation for low-resourced languages embedded with language identification

Author: Sefara, Tshephisho J ; Zwane, SG ; Gama, N ; Sibisi, H ; Senoamadi, PN ; Marivate, V Date: Apr 2021 Recent research on the development of machine translation (MT) models has resulted in state-of-the-art performance for many resourced European languages. However, there has been a little focus on applying these MT services to low-resourced ... Read more

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