Developments of Swahili resources for an automatic speech recognition system
By H. Gelas, Laurent Besacier, François Pellegrino. 2012
65 citations recorded by the source corpus.
Subfields: Natural Language Processing, Speech & Audio
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Alexei Baevski
- Michael Auli
- Abdel-rahman Mohamed
- Wei-Ning Hsu
- Graham Neubig
- Alexis Conneau
- Luke S. Zettlemoyer
- Hung-yi Lee
In Speech & Audio
- Wei-Ning Hsu
- Abdel-rahman Mohamed
- Alexei Baevski
- Michael Auli
- Hung-yi Lee
- Alexis Conneau
- Jinyu Li
- James R. Glass
Citations in the corpus
- Unsupervised Speech Recognition (2021, methodology): “We experiment with the Swahili data from the ALFFA project (Gelas et al., 2012; Abate et al., 2005; Tachbelie et al., 2014) which is read speech.”
- Self-Supervised Speech Representation Learning: A Review (2022, background): “The ALFFA project3 collects speech of African languages to promote the development of speech technologies in Africa, and [123] leverages four African languages collected in the project for evaluation: Amharic [241], Fongbe [242], Swahili [243], and”
- Speech technologies for african languages: example of a multilingual calculator for education (2015, background): “More details on the Swahili corpus and how it was collected can be found on [2].”
- Morfessor 2.0: Python Implementation and Extensions for Morfessor Baseline (2013, methodology): “…in natural language processing applications such as speech recognition (e.g. Hirsimäki et al., 2006; Creutz et al., 2007; Mihajlik et al., 2010; Gelas et al., 2012), speech retrieval (e.g. Arisoy et al., 2009; Turunen and Kurimo, 2011), and statistical machine translation (e.g. Virpioja et…”