Connectionist Architectures for Multi-Speaker Phoneme Recognition

II, John B. Hampshire, Waibel, Alex

Neural Information Processing Systems 

We present a number of Time-Delay Neural Network (TDNN) based architectures for multi-speaker phoneme recognition (/b,d,g/ task). We use speech of two females and four males to compare the performance of the various architectures against a baseline recognition rate of 95.9% for a single IDNN on the six-speaker /b,d,g/ task.

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