Creating conversational interfaces for children is challenging in several respects. These include acoustic modeling for automatic speech recognition (ASR), language and dialog modeling, and multimodal-multimedia user interface design. First, issues in ASR of children's speech are introduced by an analysis of developmental changes in the spectral and temporal characteristics of the speech signal using data obtained from 456 children, ages five to 18 years. Acoustic modeling adaptation and vocal tract normalization algorithms that yielded state-of-the-art ASR performance on children's speech are described. Second, an experiment designed to better understand how children interact with machines using spoken language is described. Realistic conversational multimedia interaction data were obtained from 160 children who played a voice-activated computer game in a Wizard of Oz (WoZ) scenario. Results of using these data in developing novel language and dialog models as well as in a unified maximum likelihood framework for acoustic decoding in ASR and semantic classification for spoken language understanding are described. Leveraging the lessons learned from the WoZ study and a concurrent user experience evaluation, a multimedia personal agent prototype for children was designed. Details of the architecture and application details are described. Informal evaluation by children was found positive especially for the animated agent and the speech interface.