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Pitch modelling for the Nguni languages

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dc.contributor.author Govender, Natasha
dc.contributor.author Barnard, E
dc.contributor.author Davel, MH
dc.date.accessioned 2012-02-15T13:13:58Z
dc.date.available 2012-02-15T13:13:58Z
dc.date.issued 2007-06
dc.identifier.citation Govender, N., Barnard, E. and Davel, M.H. 2007. Pitch modelling for the Nguni languages. South African Computer Journal, vol. 38, pp 28-39 en_US
dc.identifier.issn 1015-7999
dc.identifier.uri http://hdl.handle.net/10204/5574
dc.description Copyright: 2007, The authors. en_US
dc.description.abstract Although the complexity of prosody is widely recognised, the lack of widely-accepted descriptive standards for prosodic phenomena has meant that prosodic systems for most of the languages of the world have, at best, been described in impressionistic rule-based terms. For the languages of Southern Africa, the deficiencies in our modelling capabilities are acute. Little work of a quantitative nature has been published for the languages of the Nguni family (such as isiZulu and isiXhosa), and there are significant contradictions and imprecisions in the literature on this topic, which partially stems from the lack of quantitative, measurement-driven analysis. This paper therefore embarks on a programme aimed at understanding the relationship between linguistic and physical variables of a prosodic nature in this family of languages. Firstly we undertake a set of experiments to select an appropriate pitch tracking algorithm for the the Nguni family of languages. We then use this pitch tracking algorithm to extract relevant data from speech recordings to build intonation corpora for isiZulu and isiXhosa. Using the extracted data in the intonation corpus, we show that it is possible to develop fairly accurate intonation models using a neural network classifier for isiZulu and isiXhosa. en_US
dc.language.iso en en_US
dc.publisher Sabinet Online en_US
dc.subject Prosody en_US
dc.subject Nguni languages en_US
dc.subject Fundamental frequency en_US
dc.subject Pitch tracking en_US
dc.subject Intonation corpus en_US
dc.subject Intonation modelling en_US
dc.title Pitch modelling for the Nguni languages en_US
dc.type Article en_US
dc.identifier.apacitation Govender, N., Barnard, E., & Davel, M. (2007). Pitch modelling for the Nguni languages. http://hdl.handle.net/10204/5574 en_ZA
dc.identifier.chicagocitation Govender, Natasha, E Barnard, and MH Davel "Pitch modelling for the Nguni languages." (2007) http://hdl.handle.net/10204/5574 en_ZA
dc.identifier.vancouvercitation Govender N, Barnard E, Davel M. Pitch modelling for the Nguni languages. 2007; http://hdl.handle.net/10204/5574. en_ZA
dc.identifier.ris TY - Article AU - Govender, Natasha AU - Barnard, E AU - Davel, MH AB - Although the complexity of prosody is widely recognised, the lack of widely-accepted descriptive standards for prosodic phenomena has meant that prosodic systems for most of the languages of the world have, at best, been described in impressionistic rule-based terms. For the languages of Southern Africa, the deficiencies in our modelling capabilities are acute. Little work of a quantitative nature has been published for the languages of the Nguni family (such as isiZulu and isiXhosa), and there are significant contradictions and imprecisions in the literature on this topic, which partially stems from the lack of quantitative, measurement-driven analysis. This paper therefore embarks on a programme aimed at understanding the relationship between linguistic and physical variables of a prosodic nature in this family of languages. Firstly we undertake a set of experiments to select an appropriate pitch tracking algorithm for the the Nguni family of languages. We then use this pitch tracking algorithm to extract relevant data from speech recordings to build intonation corpora for isiZulu and isiXhosa. Using the extracted data in the intonation corpus, we show that it is possible to develop fairly accurate intonation models using a neural network classifier for isiZulu and isiXhosa. DA - 2007-06 DB - ResearchSpace DP - CSIR KW - Prosody KW - Nguni languages KW - Fundamental frequency KW - Pitch tracking KW - Intonation corpus KW - Intonation modelling LK - https://researchspace.csir.co.za PY - 2007 SM - 1015-7999 T1 - Pitch modelling for the Nguni languages TI - Pitch modelling for the Nguni languages UR - http://hdl.handle.net/10204/5574 ER - en_ZA


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