most citedSemi-supervised acoustic modelling for five-lingual code-switched ASR using automatically-segmented soap opera speech

7 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

eess.AS20207 cited

Semi-supervised acoustic modelling for five-lingual code-switched ASR using automatically-segmented soap opera speech

N. Wilkinson, A. Biswas, E. Yılmaz +3

This paper considers the impact of automatic segmentation on the fully-automatic, semi-supervised training of automatic speech recognition (ASR) systems for five-lingual code-switc…

eess.AS20201 cited

Semi-supervised acoustic and language model training for English-isiZulu code-switched speech recognition

A. Biswas, F. de Wet, E. van der Westhuizen +1

We present an analysis of semi-supervised acoustic and language model training for English-isiZulu code-switched ASR using soap opera speech. Approximately 11 hours of untranscribe…

eess.AS2020

Semi-supervised Development of ASR Systems for Multilingual Code-switched Speech in Under-resourced Languages

Astik Biswas, Emre Yılmaz, Febe de Wet +2

This paper reports on the semi-supervised development of acoustic and language models for under-resourced, code-switched speech in five South African languages. Two approaches are…

cs.CL2019

Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training

Astik Biswas, Raghav Menon, Ewald van der Westhuizen +1

We present improvements in automatic speech recognition (ASR) for Somali, a currently extremely under-resourced language. This forms part of a continuing United Nations (UN) effort…

cs.CL2019

Semi-supervised acoustic model training for five-lingual code-switched ASR

Astik Biswas, Emre Yılmaz, Febe de Wet +2

This paper presents recent progress in the acoustic modelling of under-resourced code-switched (CS) speech in multiple South African languages. We consider two approaches. The firs…

cs.CL2019

Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks

Ryan Eloff, André Nortje, Benjamin van Niekerk +7

For our submission to the ZeroSpeech 2019 challenge, we apply discrete latent-variable neural networks to unlabelled speech and use the discovered units for speech synthesis. Unsup…