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Here we present AusKidTalk [1], an audio-visual (AV) corpus of Australian children’s speech collected to facilitate the development of speech based technological solutions for children. It builds upon the technology and expertise developed through the collection of an earlier corpus of Australian adult speech, AusTalk [2,3]. This multi-site initiative was established to remedy the dire shortage of children’s speech corpora in Australia and around the world that are sufficiently sized to train accurate automated speech processing tools for children. We are collecting ~600 hours of speech from children aged 3–12 years that includes single word and sentence productions as well as narrative and emotional speech. In this paper, we discuss the key requirements for AusKidTalk and how we designed the recording setup and protocol to meet them. We also discuss key findings from our feasibility study of the recording protocol, recording tools, and user interface.

This paper introduces a pronunciation verification method to be used in an automatic assessment therapy tool of child disordered speech. The proposed method creates a phonebased search lattice that is flexible enough to cover all probable mispronunciations. This allows us to verify the correctness of the pronunciation and detect the incorrect phonemes produced by the child. We compare between two different acoustic models, the conventional GMM-HMM and the hybrid DNN-HMM. Results show that the hybrid DNNHMM outperforms the conventional GMM-HMM for all experiments on both normal and disordered speech. The total correctness accuracy of the system at the phoneme level is above 85% when used with disordered speech.