“would you buy a car from me?” - on the likability of telephone voices

We researched how “likable ” or “pleasant ” a speaker appears based on a subset of the “Agender ” database which was recently introduced at the 2010 Interspeech Paralinguistic Challenge. 32 participants rated the stimuli according to their likability on a seven point scale. An Anova showed that the samples rated are significantly different although the inter-rater agreement is not very high. Experiments with automatic regression and clas-sification by REPTree ensemble learning resulted in a cross-correlation of up to.378 with the evaluator weighted estimator, and 67.6 % accuracy in binary classification (likable / not lik-able). Analysis of individual acoustic feature groups reveals that for this data, auditory spectral features seem to contribute the most to reliable automatic likability analysis. Index Terms: speaker traits, likability, classification 1.