| Schäuble, P. and Wechsler, M. "First Experiences with a System for Content Based Retrieval of Information from Speech Recordings," IJCAI-95 Workshop on Intelligent Multimedia Information Retrieval, Maybury, M. T., (chair), working notes, pp. 59 - 69, August, 1995. |
....and the service does not include news sources other than CNN. In addition, CNN AT WORK does not feature an integrated multi modal query interface [CNN AT WORK95] Preliminary investigation into the use of speech recognition for analysis of a news story was carried out by Sch uble and Wechsler [Sch uble95]. Since they lacked a powerful speech recognizer, their approach used a phonetic engine that transformed the spoken content of the news stories into possibly erroneous phoneme strings. The query was also transformed into a phoneme string and the database searched for the best approximate match. ....
....recognition generated transcripts are less focused on the correct topic and are more likely to be displaced by other apparently relevant stories from the distractor set. Experiment 4: Phonetic transcription compared with large vocabulary recognition In previous work, Sch uble and Wechsler [Sch uble95] performed experiments in which they used automatic phonetic transcriptions, as opposed to the whole word speech recognition transcripts described above, for information retrieval in a small radio news corpus. They reported reasonable success in retrieving relevant documents. Similarly, Jones et ....
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Schäuble, P. and Wechsler, M. "First Experiences with a System for Content Based Retrieval of Information from Speech Recordings," IJCAI-95 Workshop on Intelligent Multimedia Information Retrieval, Maybury, M. T., (chair), working notes, pp. 59 - 69, August, 1995.
....the reduction of nineteen percent caused by using speech recognizer output. Experiments done at Cambridge [3,4] have suggested that word spotting can help overcome the OOV problem. Instead of word spotting, we used a phonetic sub string matching technique first suggested by Sch uble and Wechsler [8]. TFIDF stop words (base) Full system with all IR features (best) Type of transcription Average Precision of Text retrieval Average Precision of Text retrieval Words from Text 0.570 100 0.799 100 Words from SR 0.330 58 0.644 81 Words from Text without words not in SR dictionary ....
Schäuble, P. and Wechsler, M., "First Experiences with a System for Content Based Retrieval of Information from Speech Recordings," IJCAI-95 Workshop on Intelligent Multimedia Information Retrieval, Maybury, M. T., (chair), working notes, pp. 59-69, August, 1995.
No context found.
Schäuble, P. and Wechsler, M., "First Experiences with a System for Content Based Retrieval of Information from Speech Recordings," IJCAI-95 Workshop on Intelligent Multimedia Information Retrieval, Maybury, M. T., (chair), working notes, pp. 59 - 69, August, 1995.
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