177 citations · 251 across the 20 of their papers we have counts for
21 papers
The ÌròyìnSpeech Text Corpus: 24,905 Curated Yorùbá Sentences for Speech and Language Technology
Kola Tubosun, Aanuoluwapo Aremu, Tolulope Ogunremi +2
ÌròyìnSpeech is a 42-hour, 80-speaker Yorùbá read-speech corpus whose audio has been distributed by ELRA since 2024. This paper describes the release of its text component: 24,905…
Zero-Shot Crate Digging: DJ Tool Retrieval Using Speech Activity, Music Structure And CLAP Embeddings
Iroro Orife
In genres like Hip-Hop, RnB, Reggae, Dancehall and just about every Electronic/Dance/Club style, DJ tools are a special set of audio files curated to heighten the DJ's musical perf…
Facing the Music: Tackling Singing Voice Separation in Cinematic Audio Source Separation
Karn N. Watcharasupat, Chih-Wei Wu, Iroro Orife
Cinematic audio source separation (CASS), as a standalone problem of extracting individual stems from their mixture, is a fairly new subtask of audio source separation. A typical s…
Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Support
Karn N. Watcharasupat, Chih-Wei Wu, Iroro Orife
Cinematic audio source separation (CASS), as a problem of extracting the dialogue, music, and effects stems from their mixture, is a relatively new subtask of audio source separati…
A Generalized Bandsplit Neural Network for Cinematic Audio Source Separation
Karn N. Watcharasupat, Chih-Wei Wu, Yiwei Ding +6
Cinematic audio source separation is a relatively new subtask of audio source separation, with the aim of extracting the dialogue, music, and effects stems from their mixture. In t…
ÌròyìnSpeech: A multi-purpose Yorùbá Speech Corpus
Tolulope Ogunremi, Kola Tubosun, Anuoluwapo Aremu +2
We introduce ÌròyìnSpeech, a new corpus influenced by the desire to increase the amount of high quality, contemporary Yorùbá speech data, which can be used for both Text-to-Speech…
Looking Similar, Sounding Different: Leveraging Counterfactual Cross-Modal Pairs for Audiovisual Representation Learning
Nikhil Singh, Chih-Wei Wu, Iroro Orife +1
Audiovisual representation learning typically relies on the correspondence between sight and sound. However, there are often multiple audio tracks that can correspond with a visual…
BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus
Josh Meyer, David Ifeoluwa Adelani, Edresson Casanova +16
BibleTTS is a large, high-quality, open speech dataset for ten languages spoken in Sub-Saharan Africa. The corpus contains up to 86 hours of aligned, studio quality 48kHz single sp…
Learning Nigerian accent embeddings from speech: preliminary results based on SautiDB-Naija corpus
Tejumade Afonja, Oladimeji Mudele, Iroro Orife +6
This paper describes foundational efforts with SautiDB-Naija, a novel corpus of non-native (L2) Nigerian English speech. We describe how the corpus was created and curated as well…
AVASpeech-SMAD: A Strongly Labelled Speech and Music Activity Detection Dataset with Label Co-Occurrence
Yun-Ning Hung, Karn N. Watcharasupat, Chih-Wei Wu +4
We propose a dataset, AVASpeech-SMAD, to assist speech and music activity detection research. With frame-level music labels, the proposed dataset extends the existing AVASpeech dat…
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
Julia Kreutzer, Isaac Caswell, Lisa Wang +49
With the success of large-scale pre-training and multilingual modeling in Natural Language Processing (NLP), recent years have seen a proliferation of large, web-mined text dataset…
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named en…
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila +45
Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a compl…
Towards Neural Machine Translation for Edoid Languages
Iroro Orife
Many Nigerian languages have relinquished their previous prestige and purpose in modern society to English and Nigerian Pidgin. For the millions of L1 speakers of indigenous langua…
Improving Yorùbá Diacritic Restoration
Iroro Orife, David I. Adelani, Timi Fasubaa +4
Yorùbá is a widely spoken West African language with a writing system rich in orthographic and tonal diacritics. They provide morphological information, are crucial for lexical dis…
Masakhane -- Machine Translation For Africa
Iroro Orife, Julia Kreutzer, Blessing Sibanda +22
Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is du…
Audio Spectrogram Factorization for Classification of Telephony Signals below the Auditory Threshold
Iroro Orife, Shane Walker, Jason Flaks
Traffic Pumping attacks are a form of high-volume SPAM that target telephone networks, defraud customers and squander telephony resources. One type of call in these attacks is char…
The Marchex 2018 English Conversational Telephone Speech Recognition System
Seongjun Hahm, Iroro Orife, Shane Walker +1
In this paper, we describe recent performance improvements to the production Marchex speech recognition system for our spontaneous customer-to-business telephone conversations. In…
Attentive Sequence-to-Sequence Learning for Diacritic Restoration of Yorùbá Language Text
Iroro Orife
Yorùbá is a widely spoken West African language with a writing system rich in tonal and orthographic diacritics. With very few exceptions, diacritics are omitted from electronic te…
Semi-Supervised Model Training for Unbounded Conversational Speech Recognition
Shane Walker, Morten Pedersen, Iroro Orife +1
For conversational large-vocabulary continuous speech recognition (LVCSR) tasks, up to about two thousand hours of audio is commonly used to train state of the art models. Collecti…
Riddim: A Rhythm Analysis and Decomposition Tool Based On Independent Subspace Analysis
Iroro Orife
The goal of this thesis was to implement a tool that, given a digital audio input, can extract and represent rhythm and musical time. The purpose of the tool is to help develop bet…