- Abstract:
-
This paper presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words, with each word being identified by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems, as well as human transcriptions of voicemail speech.
- Links To Paper
- 1st Link
- 2nd Link
- Bibtex format
- @Article{EDI-INF-RR-0658,
- author = {
Steve Renals
and Konstantinos Koumpis
},
- title = {Automatic summarization of voicemail messages using lexical and prosodic features},
- journal = {ACM Transactions on Speech and Language Processing},
- publisher = {ACM Press},
- year = 2005,
- month = {Feb},
- volume = {2(1)},
- pages = {1-24},
- doi = {10.1145/1075389.1075390},
- url = {http://doi.acm.org/10.1145/1075389.1075390},
- }
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