Speaker-independent word recognition using dynamic programming neural networks
Hiroaki Sakoe, Ryosuke Isotani, Kazunaga Yoshida, K.-I. Iso, Takao Watanabe · International Conference on Acoustics, Speech, and Signal Processing · 2003
A description is given of speaker-independent word recognition based on a new neural network model called the dynamic programming neural network (DNN), which can treat time-sequence patterns. DNN is based on the integration of a multilayer neural network and dynamic-programming-based matching. Speaker-independent isolated Japanese digit recognition experiments were carried out using data uttered by 107 speakers (50 speakers for training and 57 speakers for testing). The recognition accuracy was 99.3%, suggesting that the model can be effective for speech recognition.>