A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Prosody in Speech Understanding Systems
Prosody in Speech Understanding Systems
Thematic indexing of spoken documents by using self-organizing maps
Speech Communication
SARDSRN: a neural network shift-reduce parser
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Using semantic analysis to improve speech recognition performance
Computer Speech and Language
| Hi-index | 0.00 |
Recent neurocognitive researches demonstrate how the natural processing of auditory sentences occurs. Nowadays, there is not an appropriate human-computer speech interaction, and this constitutes a computational challenge to be overtaked. In this direction, we propose a speech comprehension software architecture to represent the flow of this neurocognitive model. In this architecture, the first step is the speech signal processing to written words and prosody coding. Afterwards, this coding is used as input in syntactic and prosodic-semantic analyses. Both analyses are done concomitantly and their outputs are matched to verify the best result. The computational implementation applies wavelets transforms to speech signal codification and data prosodic extraction and connectionist models to syntactic parsing and prosodic-semantic mapping.