Eno-Abasi Urua
University of Uyo
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Featured researches published by Eno-Abasi Urua.
Speech Communication | 2014
Moses Ekpenyong; Eno-Abasi Urua; Oliver Watts; Simon King; Junichi Yamagishi
Ibibio is a Nigerian tone language, spoken in the south-east coastal region of Nigeria. Like most African languages, it is resource-limited. This presents a major challenge to conventional approaches to speech synthesis, which typically require the training of numerous predictive models of linguistic features such as the phoneme sequence (i.e., a pronunciation dictionary plus a letter-to-sound model) and prosodic structure (e.g., a phrase break predictor). This training is invariably supervised, requiring a corpus of training data labelled with the linguistic feature to be predicted. In this paper, we investigate what can be achieved in the absence of many of these expensive resources, and also with a limited amount of speech recordings. We employ a statistical parametric method, because this has been found to offer good performance even on small corpora, and because it is able to directly learn the relationship between acoustics and whatever linguistic features are available, potentially mitigating the absence of explicit representations of intermediate linguistic layers such as prosody. We present an evaluation that compares systems that have access to varying degrees of linguistic structure. The simplest system only uses phonetic context (quinphones), and this is compared to systems with access to a richer set of context features, with or without tone marking. It is found that the use of tone marking contributes significantly to the quality of synthetic speech. Future work should therefore address the problem of tone assignment using a dictionary and the building of a prediction module for out-of-vocabulary words.
International Journal of Speech Technology | 2008
Moses Ekpenyong; Eno-Abasi Urua; Dafydd Gibbon
In this paper we discuss the procedural problems, issues and challenges involved in developing a generic speech synthesizer for African tone languages. We base our development methodology on the “MultiSyn” unit-selection approach, supported by Festival Text-To-Speech (TTS) Toolkit for Ibibio, a Lower Cross subgroup of the (New) Benue-Congo language family widely spoken in the southeastern region of Nigeria. We present in a chronological order, the several levels of infrastructural and linguistic problems as well as challenges identified in the Local Language Speech Technology Initiative (LLSTI) during the development process (from the corpus preparation and refinement stage to the integration and synthesis stage). We provide solutions to most of these challenges and point to possible outlook for further refinement. The evaluation of the initial prototype shows that the synthesis system will be useful to non-literate communities and a wide spectrum of applications.
Archive | 2018
Moses Ekpenyong; Udoinyang G. Inyang; Mercy E. Edoho; Eno-Abasi Urua
An extensive study on intra-speaker variability is presented in this chapter. The chapter is organized as follows: Section 2.1 gives a succinct background on speaker recognition and recent applications. Section 2.2 reviews related works on speaker perception, channel variability, as well as clustering and visualization. Section 2.3 provides an in-depth discussion on the phonology (study of sound patterns and their meanings) of Ibibio – a low-resourced language – spoken in the Southeast coastal region of Nigeria, West Africa – and used in this study to demonstrate intra-speaker variability. Section 2.4 is the methodology of the study and includes: the system’s architecture, utterance dataset formation, participants/speakers selection – speech recording – speech signal dataset processing, speech feature extraction, and speech feature dataset construction. Section 2.5 presents the results obtained from (i) a frame-by-frame analysis, (ii) principal component analysis (PCA), and (iii) self-organizing map (SOM) clustering and visualization – on the extracted speech features (duration, F0, intensity, formants, pulses and MFCC: mel-cepstral coefficient). The chapter ends with a conclusion and pointer to future research direction.
language and technology conference | 2011
Moses Ekpenyong; Emem Obong Udoh; Escor Udosen; Eno-Abasi Urua
In this contribution, we document the series of progress towards attaining a generic and replicable system that is applicable not only to Nigerian languages but also other African languages. The current system implements a state-of-the-art approach called the Hidden Markov Model (HMM) approach and aims at a hybridised version which front end components would serve other NLP tasks, as well as future research and developments. We continue to tackle the language specific problems and the ‘unity of purpose’ phenomenon for tone language systems and improve on the speech quality as an extension of our LTC’2011 paper. Specifically, we address issues bordering on tone modelling using syllables as basic synthesis units, with an ‘eye ball’ assessment of the synthesised speech quality. The results of this research offer hope for further improvements, and we envisage an unsupervised system to minimise the labour intensive aspects of the current design. Also, with the active collaboration network established in the course of this research, we are certain that a more robust system that would serve a wide variety of applications will evolve.
Studies in African linguistics | 1999
Eno-Abasi Urua
language resources and evaluation | 2004
Dafydd Gibbon; Firmin Ahoua; Eddi Gbéry; Eno-Abasi Urua; Moses Ekpenyong
Archive | 2003
Eno-Abasi Urua; Dafydd Gibbon; Ulrike Gut
Telecommunication Systems | 2013
Moses Ekpenyong; Eno-Abasi Urua
Archive | 2006
Dafydd Gibbon; Eno-Abasi Urua
Archive | 2009
Moses Ekpenyong; Mfon Udoinyang; Eno-Abasi Urua