Paper: Imposing Hierarchical Browsing Structures onto Spoken Documents

ACL ID C10-2177
Title Imposing Hierarchical Browsing Structures onto Spoken Documents
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

This paper studies the problem of im- posing a known hierarchical structure onto an unstructured spoken document, aiming to help browse such archives. We formulate our solutions within a dynamic-programming-based alignment framework and use minimum error- rate training to combine a number of global and hierarchical constraints. This pragmatic approach is computationally efficient. Results show that it outperforms a baseline that ignores the hierarchical and global features and the improvement is consistent on transcripts with different WERs. Directly imposing such hierar- chical structures onto raw speech without using transcripts yields competitive results.