Speechfind for CDP: Advances in spoken document retrieval for the U. S. collaborative digitization program

This paper presents our recent advances for SpeechFind, a CRSS-UTD designed spoken document retrieval system for the U.S. based Collaborative Digitization Program (CDP). A proto-type of SpeechFind for the CDP is currently serving as the search engine for 1,300 hours of CDP audio content which contain a wide range of acoustic conditions, vocabulary and period selection, and topics. In an effort to determine the amount of user corrected transcripts needed to impact automatic speech recognition (ASR) and audio search, a web-based online interface for verification of ASR-generated transcripts was developed. The procedure for enhancing the transcription performance for SpeechFind is also presented. A selection of adaptation methods for language and acoustic models are employed depending on the acoustics of the corpora under test. Experimental results on the CDP corpus demonstrate that the employed model adaptation scheme using the verified transcripts is effective in improving recognition accuracy. Through a combination of feature/acoustic model enhancement and language model selection, up to 24.8% relative improvement in ASR was obtained. The SpeechFind system, employing automatic transcript generation, online CDP transcript correction, and our transcript reliability estimator, demonstrates a comprehensive support mechanism to ensure reliable transcription and search for U.S. libraries with limited speech technology experience.