Speech, Emotion, Age, Language, Task, and Typicality: Trying to Disentangle Performance and Feature Relevance

摘要

The availability of speech corpora is positively correlated with typicality: The more typical the population is we draw our sample from, the easier it is to get enough data. The less typical the envisaged population is, the more difficult it is to get enough data. Children with Autism Spectrum Condition are atypical in several respect: They are children, they might have problems with an experimental setting where their speech should be recorded, and they belong to a specific subgroup of children. Thus we address two possible strategies: First, we analyse the feature relevance for samples taken from different populations, this is not directly improving performances but we found additional specific features within specific groups. Second, we perform cross-corpus experiments to evaluate if enriching the training data with data obtained from similar populations can increase classification performances. In this pilot study we therefore use four different samples of speakers, all of them producing one and the same emotion and in addition, the neutral state. We used two publicly available databases, the Berlin Emotional Speech database and the FAU Aibo Corpus, in addition to our own ASC-Inclusion database.