17. A data process unit comprising: an acoustic space storing unit for storing an acoustic space composed of a plurality of first pattern models, which are generated from first speech data of a plurality of speakers, and each of which has first 4-dimensional or higher dimensional feature data; a speech data acquiring unit for acquiring second speech data of a target speaker; a position calculating unit for: converting the second speech data into second 4-dimensional or higher dimensional feature data, generating a second pattern model to correspond to the second speech data based on the second 4-dimensional or higher dimensional feature data, calculating a mathematical distance between the second pattern model and the first pattern models based on the second 4-dimensional or higher dimensional feature data and the first 4-dimensional or higher dimensional feature data, and calculating a position of the second speech data in the acoustic space based on the mathematical distance; a similar-speaker detecting unit for detecting a similar speaker who is similar in speech to the target speaker out of the speakers, based on the position of the second speech data and the first pattern models; and a positional relationship information display unit for displaying information representing a positional relationship between the second speech data and a third pattern model of the similar speaker in the acoustic space, on a two-dimensional plane or in a three-dimensional space with a relationship of the mathematical distance being maintained, based on the position of the second speech data, wherein the second pattern model and the first pattern models are generated by using Hidden Markov Models (HMM), and wherein the mathematical distance is calculated according to Euclidean distance determined based on a mean vector normalized by a product of standard deviations of normal distributions between the second pattern model and the first pattern models.
17. A data process unit comprising: an acoustic space storing unit for storing an acoustic space composed of a plurality of first pattern models, which are generated from first speech data of a plurality of speakers, and each of which has first 4-dimensional or higher dimensional feature data; a speech data acquiring unit for acquiring second speech data of a target speaker; a position calculating unit for: converting the second speech data into second 4-dimensional or higher dimensional feature data, generating a second pattern model to correspond to the second speech data based on the second 4-dimensional or higher dimensional feature data, calculating a mathematical distance between the second pattern model and the first pattern models based on the second 4-dimensional or higher dimensional feature data and the first 4-dimensional or higher dimensional feature data, and calculating a position of the second speech data in the acoustic space based on the mathematical distance; a similar-speaker detecting unit for detecting a similar speaker who is similar in speech to the target speaker out of the speakers, based on the position of the second speech data and the first pattern models; and a positional relationship information display unit for displaying information representing a positional relationship between the second speech data and a third pattern model of the similar speaker in the acoustic space, on a two-dimensional plane or in a three-dimensional space with a relationship of the mathematical distance being maintained, based on the position of the second speech data, wherein the second pattern model and the first pattern models are generated by using Hidden Markov Models (HMM), and wherein the mathematical distance is calculated according to Euclidean distance determined based on a mean vector normalized by a product of standard deviations of normal distributions between the second pattern model and the first pattern models. 23. The data process unit according to claim 17 , wherein the second pattern model is a pattern model selected from the first pattern models, based on a likelihood of the second 4-dimensional or higher dimensional feature, and the first pattern models.