English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

A New Workflow for Semi-automatized Annotations: Tests with Long-Form Naturalistic Recordings of Childrens Language Environments

MPS-Authors
/persons/resource/persons84362

Casillas,  Marisa
Language Development Department, MPI for Psycholinguistics, Max Planck Society;

/persons/resource/persons172

Sloetjes,  Han
The Language Archive, MPI for Psycholinguistics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

Casillas_etal_2017a.PDF
(Publisher version), 307KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Casillas, M., Bergelson, E., Warlaumont, A. S., Cristia, A., Soderstrom, M., VanDam, M., et al. (2017). A New Workflow for Semi-automatized Annotations: Tests with Long-Form Naturalistic Recordings of Childrens Language Environments. In Proceedings of Interspeech 2017 (pp. 2098-2102). doi:10.21437/Interspeech.2017-1418.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002D-57E4-A
Abstract
Interoperable annotation formats are fundamental to the utility, expansion, and sustainability of collective data repositories.In language development research, shared annotation schemes have been critical to facilitating the transition from raw acoustic data to searchable, structured corpora. Current schemes typically require comprehensive and manual annotation of utterance boundaries and orthographic speech content, with an additional, optional range of tags of interest. These schemes have been enormously successful for datasets on the scale of dozens of recording hours but are untenable for long-format recording corpora, which routinely contain hundreds to thousands of audio hours. Long-format corpora would benefit greatly from (semi-)automated analyses, both on the earliest steps of annotation—voice activity detection, utterance segmentation, and speaker diarization—as well as later steps—e.g., classification-based codes such as child-vs-adult-directed speech, and speech recognition to produce phonetic/orthographic representations. We present an annotation workflow specifically designed for long-format corpora which can be tailored by individual researchers and which interfaces with the current dominant scheme for short-format recordings. The workflow allows semi-automated annotation and analyses at higher linguistic levels. We give one example of how the workflow has been successfully implemented in a large cross-database project.