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This paper describes a new method of implementing mixed-initiative spoken dialogue systems based on parallel computing architecture. In a mixed-initiative dialogue, the user as well as the system needs to be capable of controlling the dialogue sequence. In our implementation, various language models corresponding to different dialogue contents, such as requests for information or replies to the system, are built and multiple recognizers using these language models are driven under a parallel computing architecture. The dialogue content of the user is automatically detected based on likelihood scores given by the recognizers, and the content is used to build the dialogue. A transitional probability from one dialogue state uttering a kind of content to another state uttering a different content is incorporated into the likelihood score. A flexible dialogue structure that gives users the initiative to control the dialogue is implemented by this architecture. Real-time dialogue systems for retrieving information about restaurants and food stores are built and evaluated in terms of dialogue content identification rate and keyword accuracy. The proposed architecture has the advantage that the dialogue system can be easily modified without remaking the whole language model.