{'fraction_non_alphanumeric': 0.011904761904761904, 'fraction_numerical': 0.0, 'mean_word_length': 5.902985074626866, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
SPEECH RECOGNITION AND INFORMATION RETRIEVAL: EXPERIMENTS IN RETRIEVING SPOKEN DOCUMENTS

The Informedia Digital Video Library Project at Carnegie Mellon University is making large corpora of video and audio data available for full content retrieval by integrating natural language understanding, image processing, speech recognition and information retrieval. Information retrieval of from corpora of speech recognition output is critical to the project’s success. In this paper, we outline how this output is combined information from other modalities to produce a successful interface. We then describe experiments that compare retrieval effectiveness on spoken and text documents and investigate the sources of retrieval errors on the former. Finally we investigate how improvements in speech recognizer accuracy may affect retrieval, and whether retrieval will still be effective when larger spoken corpora are indexed.