1. An apparatus for calculating a posteriori probabilities of phoneme symbols, comprising: feature extracting means for extracting speech feature parameters from a speech signal of an uttered speech sentence composed of an inputted character series; and calculating means for calculating a a posteriori probability of a phoneme symbol of the speech signal, by using a bidirectional recurrent neural network, wherein said bidirectional recurrent neural network comprises: an input layer for receiving, as input signals, the speech feature parameters extracted by the feature extracting means and a plurality of hypothetical phoneme symbol series signals; an intermediate layer of at least one layer having a plurality of units; and an output layer for outputting a a posteriori probability of each phoneme symbol, wherein said input layer comprises: a first input neuron group having a plurality of units, for receiving, as input signals, a plurality of speech feature parameters and a plurality of phoneme symbol series signals; a forward module; and a backward module, wherein said forward module has a forward-in-time feedback connection, and generates and outputs to said intermediate layer, a plurality of parameters of a timing delayed by a predetermined unit time from a plurality of parameters outputted from said first input neuron group, based on a plurality of speech feature parameters and a plurality of phoneme symbol series signals, and wherein said backward module has a backward-in-time feedback connection, and generates and outputs to said intermediate layer, a plurality of parameters of a timing inversely delayed by a predetermined unit timing from a plurality of parameters outputted from said first input neuron group, based on a plurality of speech feature parameters.