In this paper we introduce a Phone Vector Discrete HMM (PVDHMM) that decodes a phone recognizer's output. The proposed PVDHMM treats a phone recognizer as a vector quantizer whose codebook size is equal to the size of its phone set. To examine the proposed method we perform two experiments. First, the output of a phone recognizer is recognized by the PVDHMM, and its results are compared with those of a continuous speech recognizer (CSR). Second, to investigate its potential application in the field of open-vocabulary spoken document retrieval, a retrieval experiment through word spotting is carried out on the output of a phone recognizer, and its results are compared with those of retrieval through the phone-based vector space model.