Human and automatic speech recognition in the presence of speech-intrinsic variations [Elektronische Ressource] / Bernd T. Meyer

Human and automatic speech recognition inthe presence of speech-intrinsic variationsVon der Fakult¨ at fur¨ Mathematik und Naturwissenschaftender Carl-von-Ossietzky-Universit¨ at Oldenburgzur Erlangung des Grades und Titels einesDoktors der Naturwissenschaften (Dr. rer. nat.)angenommene DissertationDipl.-Phys. Bernd T. Meyergeboren am 9. September 1978in Haselunne¨Gutachter: Prof. Dr. Dr. Birger KollmeierZweitgutachter: PD Dr. Volker HohmannTag der Disputation: 18.12.2009iiAbstractDespite several decades of research, automatic speech recognition (ASR) lacks theperformance achieved by human listeners. One of the major challenges in ASR is tocope with the immense variability of spoken language, which can be categorized intoextrinsic sources (e.g., additive noise) and intrinsic factors (such as speaking rate, style,effort, dialect, and accent). What can we learn from the biological blueprint, and whichcues important in human speech recognition (HSR) should be considered to improveASR performance? The scope of this thesis is to answer these questions by comparingthe HSR and ASR performance and - based on these results - to suggest an alternativeway of feature extraction to improve ASR. The comparison is based on the OldenburgLogatome Corpus, which is a database that contains simple nonsense words consistingof phoneme triplets and which covers the intrinsic variations mentioned above.