2005 Johns Hopkins Summer Workshop Final Report on Parsing and Spoken Structural Event Detection

This project investigated the interaction between parsing and the detection of structural metadata in conversational speech, including sentence boundaries, edits (the reparandum portion of speech repairs), and fillers. In terms of parsing, we explored alternative methods of exploiting metadata information in parsing models and measured how varying accuracy in transcription and metadata information affects parsing accuracy. In the other direction, we similarly considered how syntactic and prosodic knowledge could be leveraged in metadata detection, measuring how this knowledge impacts metadata detection accuracy. As part of this work, we investigated metrics for evaluating parse accuracy in the presence of transcription and metadata detection errors, and we report on our experience using these metrics with several parsers and across varying experimental conditions. A range of methods for handling edits during parsing were evaluated in this research (excision, addition of markups to the input string, and grammar modification). We also developed a ToBI (a prosodic structure annotation scheme [SBP + 92]) prosodic event classifier and describe its evaluation. Finally, we present methods for effective n-best sentence boundary candidate generation and reranking using syntactic, prosodic, and other features. These studies are complemented by a second set of reranking investigations wherein we optimize sentence boundar