Browsing Faculty of Engineering by Author "Kleynhans, Neil"

Now showing items 1-6 of 6

    • Code-switched English pronunciation modeling for Swahili spoken term detection 

      Kleynhans, Neil; Hartman, William; Van Niekerk, Daniel; Van Heerden, Charl; Schwartz, Rich; Tsakalidis, Stavros; Davel, Marelie H. (Procedia Computer Science: Spoken Language Technology for Under-resourced Languages, 2016-05)
      We investigate modeling strategies for English code-switched words as found in a Swahili spoken term detection system. Code switching, where speakers switch language in a conversation, occurs frequently in multilingual ...

    • Cross-bandwidth adaptation for ASR systems 

      Kleynhans, Neil; Barnard, Etienne (Pattern recognition association of South Africa (PRASA), 2013)
      Mismatches between application and training data greatly reduce the performance of automatic speech recognition (ASR) systems. However, collecting suitable amounts of in-domain and application-specific data for training ...

    • Efficient data selection for ASR 

      Kleynhans, Neil; Barnard, Etienne (Language Resources and Evaluation, 2015)
      Automatic speech recognition (ASR) technology has matured over the past few decades and has made significant impacts in a variety of fields, from assistive technologies to commercial products. However, ASR system development ...

    • Improving the Lwazi ASR baseline 

      Van Heerden, Charl; Kleynhans, Neil; Davel, Marelie H. (Interspeech 2016, 2016)
      We investigate the impact of recent advances in speech recognition techniques for under-resourced languages. Specifically, we review earlier results published on the Lwazi ASR corpus of South African languages, and ...

    • Spoken language identification system adaptation in under-resourced environments 

      Kleynhans, Neil; Barnard, Etienne (Pattern recognition association of South Africa (PRASA), 2013)
      Speech technologies have matured over the past few decades and have made significant impacts in a variety of fields, from assistive technologies to personal assistants. However, speech system development is a resource ...

    • Unsupervised acoustic model training: comparing South African English and isiZulu 

      Kleynhans, Neil; De Wet, Febe; Barnard, Etienne (IEEE, 2015)
      Large amounts of untranscribed audio data are generated every day. These audio resources can be used to develop robust acoustic models that can be used in a variety of speech-based systems. Manually transcribing this ...