Vergyri, D., Stolcke, A., Gadde, V. R. R., Ferrer, L., & Shriberg, E. (2003, April). Prosodic knowledge sources for automatic speech recognition. In 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP’03). (Vol. 1, pp. I-I). IEEE.
In this work, different prosodic knowledge sources are integrated into a state-of-the-art large vocabulary speech recognition system. Prosody manifests itself on different levels in the speech signal: within the words as a change in phone durations and pitch, inbetween the words as a variation in the pause length, and beyond the words, correlating with higher linguistic structures and nonlexical phenomena. We investigate three models, each exploiting a different level of prosodic information, in rescoring N-best hypotheses according to how well recognized words correspond to prosodic features of the utterance. Experiments on the Switchboard corpus show word accuracy improvements with each prosodic knowledge source. A further improvement is observed with the combination of all models, demonstrating that they each capture somewhat different prosodic characteristics of the speech signal.