Automatic Speech Recognition of English-isiZulu Code-switched Speech from South African Soap Operas

Abstract We introduce a new English-isiZulu code-switched speech corpus compiled from South African soap opera broadcasts. isiZulu itself is currently under-resourced, and automatic speech recognition is made even more challenging by the high prevalence of code-switching in spontaneous speech. Analysis of the corpus reflects effects common in conversational isiZulu, such as vowel deletion and cross-language prefixes and suffixes. Baseline monolingual and code-switched automatic speech recognition systems are developed, including a new language model configuration that explicitly includes switching transitions. For code-switched speech, a system with language-dependent acoustic models and language-dependent language models linked by switching transitions leads to best performance, although word error rates overall remain very high.