6. A vehicle comprising: a context model created by modeling each name included in a phone book; a model creator configured to classify the phone book according to a length of syllables of each name, and to create a context model for each length of syllables; and a voice recognizer configured to create a phone number candidate group corresponding to a received voice signal based on an acoustic model and the context model for each length of syllables, calculate a length of speech based on a Begin of Speech (BoS) and an End of Speech (EoS), and to respectively apply different reliability weight values determined according to the length of speech to phone number candidates in the phone number candidate group.
6. A vehicle comprising: a context model created by modeling each name included in a phone book; a model creator configured to classify the phone book according to a length of syllables of each name, and to create a context model for each length of syllables; and a voice recognizer configured to create a phone number candidate group corresponding to a received voice signal based on an acoustic model and the context model for each length of syllables, calculate a length of speech based on a Begin of Speech (BoS) and an End of Speech (EoS), and to respectively apply different reliability weight values determined according to the length of speech to phone number candidates in the phone number candidate group. 8. The vehicle according to claim 6 , wherein the voice recognizer applies the reliability weight values such that a phone number candidate having a length of syllables corresponding to the length of speech in the phone number candidate group has a high degree of reliability.