As one of the largest of the 11 official languages of South Africa, Zulu is spoken by approximately 9 million people. It forms part of a language family which is characterized by rich agglutinating morphological structures. This paper discusses a prototype of a computational morphological analyzer for Zulu, built by means of the Xerox finite state tools, in particular lexc and xfst. In addition to considering both the morphotactics and the morphophonological alternation rules that apply, the focus is on implementation and other issues that need to be resolved in order to produce a useful software artefact for automated morphological analysis. The current status of the prototype is alluded to by providing morphological scope, that is the various word categories (parts of speech) that may be handled, and the lexical coverage in terms of the number of different Zulu roots that are included in the embedded lexicon of the analyzer. Preliminary testing and validation procedures are briefly discussed.
This paper shows how morphological analysis contributes to solving the challenges posed by the development of a spelling checker for an agglutinative language like isiZulu. It demonstrates how the incremental implementation of affix removal rules can be used to derive word forms and enhance the lexical and error recall of the system. In the case of the spelling checker the strategies used are mainly based on the use of regular expressions, and more specifically on a process of stemming.
The development of finite-state morphological analyser prototypes for a variety of languages belonging to the Bantu language family, based on underlying machine-readable lexicons that conform to common lexical specifications and international standards.
This paper investigates the possibilities that cross-linguistic similarities and dissimilarities between related languages offer in terms of bootstrapping a morphological analyser. In this case an existing Zulu morphological analyser prototype (ZulMorph) serves as basis for a Xhosa analyser. The investigation is structured around the morphotactics and the morphophonological alternations of the languages involved. Special attention is given to the so-called "open" class, which represents the word root lexicons for specifically nouns and verbs. The acquisition and coverage of these lexicons prove to be crucial for the success of the analysers under development. The bootstrapped morphological analyser is applied to parallel test corpora and the results are discussed. A variety of cross-linguistic effects is illustrated with examples from the corpora. It is found that bootstrapping morphological analysers for languages that exhibit significant structural and lexical similarities may be fruitfully exploited for developing analysers for lesser-resourced languages.
The African Wordnet Project (AWN) aims at building wordnets for five African languages: Setswana, isiXhosa, isiZulu, Sesotho sa Leboa (also referred to as Sepedi or Northern Sotho) and Tshivenda. Currently, the so-called expand model, based on the structure of the English Princeton WordNet (PWN), is used to continually develop the African Wordnets manually. This is a labour-intensive work that needs to be performed by linguistic experts, guided by several considerations such as the level of lexicalisation of a term in the African language. Up to now, linguists were responsible for identifying and translating appropriate synsets without much help from electronic resources because in the case of African languages even basic resources such as computer readable and electronic bilingual wordlists are usually not freely available. Methods to speed up the manual development of synsets and ease the workload of the human language experts were recently investigated. These centred around utilising the minimal amount of information available in bilingual dictionaries to identify synsets in the PWN that should be included in the AWN, transferring information from dictionaries to the wordnet and presenting the potential synsets to linguists for final approval and inclusion in the wordnets. In this article, we describe the methodology developed for building the African Wordnets, a potentially significant resource for natural language processing applications. Available resources that could be taken advantage of and resources that had to be developed are investigated, and initial results and future plans are explained.
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