Summary of the paper
| Title | Transcription Methods for Consistency, Volume and Efficiency |
|---|---|
| Authors | Meghan Lammie Glenn, Stephanie M. Strassel, Haejoong Lee, Kazuaki Maeda, Ramez Zakhary and Xuansong Li |
| Abstract | This paper describes recent efforts at Linguistic Data Consortium at theUniversity of Pennsylvania to create manual transcripts as a shared resourcefor human language technology research and evaluation. Speech recognition andrelated technologies in particular call for substantial volumes of transcribedspeech for use in system development, and for human gold standard referencesfor evaluating performance over time. Over the past several years LDC hasdeveloped a number of transcription approaches to support the varied goals ofspeech technology evaluation programs in multiple languages and genres. Wedescribe each transcription method in detail, and report on the results of acomparative analysis of transcriber consistency and efficiency, for twotranscription methods in three languages and five genres. Our findings suggestthat transcripts for planned speech are generally more consistent than thosefor spontaneous speech, and that careful transcription methods result in higherrates of agreement when compared to quick transcription methods. We concludewith a general discussion of factors contributing to transcription quality,efficiency and consistency. |
| Language | |
| Topics | Corpus (creation, annotation, etc.) |
Full paper  |
Transcription Methods for Consistency, Volume and Efficiency |
| Bibtex | @InProceedings{GLENN10.849, author = {Meghan Lammie Glenn, Stephanie M. Strassel, Haejoong Lee, Kazuaki Maeda, Ramez Zakhary and Xuansong Li}, title = {Transcription Methods for Consistency, Volume and Efficiency}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |