| 摘要 |
<p>PURPOSE:To precisely recognize a speaker with a small number of learning data by inputting an internal state value and an external input value, and updating the internal state value with the input and converting it into an external output value. CONSTITUTION:This method is equipped with a speech feature extracting means 501, a neural network 502, an input value storage means 504 which stores the input of the neural network 502, and a data comparing means 503 which compares the stored input with the output. In this case, the input value storage means 504 is stored with only input data which is one frame before and compares the output data of a current frame to recognizes the speaker. Namely, a speech feature series can easily be understood from the mechanism of the generation, but the continuous motion of a speaker and a modulation organs is reflected. Then the individuality of the speaker appears as the feature of the motion, so its feature time series is processed to recognize the individual. The process is therefore performed by evaluating the individuality of the input speech by restoring the data right before the current data.</p> |
