Speech recognition of spontaneous, noisy speech using auxiliary information in Bayesian networks

Automatic speech recognition (ASR) currently performs well in the case of clean, read speech. It performs worse, however, when the speech is spontaneous and in noisy conditions. In previous work we showed the improvement that using auxiliary information in the framework of Bayesian networks (BNs) can bring to ASR in clean, read speech. Here we show that auxiliary information of pitch or rate-of-speech in the context of BNs also helps performance in spontaneous speech with noise.