  Cross-lingual speech emotion recognition is an important task for practical
applications. The performance of automatic speech emotion recognition systems
degrades in cross-corpus scenarios, particularly in scenarios involving
multiple languages or a previously unseen language such as Urdu for which
limited or no data is available. In this study, we investigate the problem of
cross-lingual emotion recognition for Urdu language and contribute URDU---the
first ever spontaneous Urdu-language speech emotion database. Evaluations are
performed using three different Western languages against Urdu and experimental
results on different possible scenarios suggest various interesting aspects for
designing more adaptive emotion recognition system for such limited languages.
In results, selecting training instances of multiple languages can deliver
comparable results to baseline and augmentation a fraction of testing language
data while training can help to boost accuracy for speech emotion recognition.
URDU data is publicly available for further research.
