For the last four decades, psycholinguistic research has dealt with the question to what extent elements of simple sentences like “The monk read the book” are planned ahead both on the abstract-lexical and phonological processing level. While a number of studies have shown that all up to the final element can be activated on these two levels, empirical evidence on the flexibility of the respective planning scopes is inconsistent, and a systematic delineation of the influence of different forms of cognitive load has not yet been provided. This thesis presents a series of 9 picture-word interference experiments in which participants produced subject-verb-object sentences while ignoring auditory distractor words. Advance planning was assessed at an abstract-lexical (lemma) level and at a phonological (word form) level under varying working memory load conditions (no load, or visuospatial load, or verbal load). In the absence of a concurrent working memory load and with a concurrent visuospatial working memory load, subject and object nouns were found to be activated at the abstract-lexical and the phonological level prior to speech onset. By contrast, with a concurrent verbal working load, the scope of advance planning at the phonological level was reduced, while the scope of advance planning at the abstract-lexical level remained unaffected. Moreover, sentence planning had a more disruptive effect on verbal working memory performance than on visuospatial working memory performance. Overall, these results suggest that advance planning at the phonological level is more adaptive to external factors than advance planning at the abstract-lexical level. Also, they indicate an overlap of resources allocated to phonological processing in speech production and verbal working memory.

For the last four decades, psycholinguistic research has dealt with the question to what extent elements of simple sentences like “The monk read the book” are planned ahead both on the abstract-lexical and phonological processing level. While a number of studies have shown that all up to the final element can be activated on these two levels, empirical evidence on the flexibility of the respective planning scopes is inconsistent, and a systematic delineation of the influence of different forms of cognitive load has not yet been provided. This thesis presents a series of 9 picture-word interference experiments in which participants produced subject-verb-object sentences while ignoring auditory distractor words. Advance planning was assessed at an abstract-lexical (lemma) level and at a phonological (word form) level under varying working memory load conditions (no load, or visuospatial load, or verbal load). In the absence of a concurrent working memory load and with a concurrent visuospatial working memory load, subject and object nouns were found to be activated at the abstract-lexical and the phonological level prior to speech onset. By contrast, with a concurrent verbal working load, the scope of advance planning at the phonological level was reduced, while the scope of advance planning at the abstract-lexical level remained unaffected. Moreover, sentence planning had a more disruptive effect on verbal working memory performance than on visuospatial working memory performance. Overall, these results suggest that advance planning at the phonological level is more adaptive to external factors than advance planning at the abstract-lexical level. Also, they indicate an overlap of resources allocated to phonological processing in speech production and verbal working memory.

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This thesis is about the effectiveness of speech features for cognitive load assessment, with particular attention being paid to new perspectives of this research area. A new cognitive load database, called CoLoSS, is introduced containing speech recordings of users who performed a learning task. Various acoustic features from different categories including prosody, voice quality, and spectrum are investigated in terms of their relevance. Moreover, Teager energy parameters, which have proven highly successful in stress detection, are introduced for cognitive load assessment and it is demonstrated how automatic speech recognition technology can be used to extract potential indicators. The suitability of the extracted features is systematically evaluated by recognition experiments with speaker-independent systems designed for discriminating between three levels of load. Additionally, a novel approach to speech-based cognitive load modelling is introduced, whereby the load is represented as a continuous quantity and its prediction can thus be regarded as a regression problem. / Die vorliegende Arbeit befasst sich mit der automatischen Erkennung von kognitiver Belastung auf Basis menschlicher Sprachmerkmale. Der Schwerpunkt liegt auf der Effektivität von akustischen Parametern, wobei die aktuelle Forschung auf diesem Gebiet um neuartige Ansätze erweitert wird. Hierzu wird ein neuer Datensatz – als CoLoSS bezeichnet – vorgestellt, welcher Sprachaufzeichnungen von Nutzern enthält und speziell auf Lernprozesse fokussiert. Zahlreiche Parameter der Prosodie, Stimmqualität und des Spektrums werden im Hinblick auf deren Relevanz analysiert. Darüber hinaus werden die Eigenschaften des Teager Energy Operators, welche typischerweise bei der Stressdetektion Verwendung finden, im Rahmen dieser Arbeit berücksichtigt. Ebenso wird gezeigt, wie automatische Spracherkennungssysteme genutzt werden können, um potenzielle Indikatoren zu extrahieren. Die Eignung der extrahierten Merkmale wird systematisch evaluiert. Dabei kommen sprecherunabhängige Klassifikationssysteme zur Unterscheidung von drei Belastungsstufen zum Einsatz. Zusätzlich wird ein neuartiger Ansatz zur sprachbasierten Modellierung der kognitiven Belastung vorgestellt, bei dem die Belastung eine kontinuierliche Größe darstellt und eine Vorhersage folglich als ein Regressionsproblem betrachtet werden kann.