Introduction
This file contains documentation on Speech Controlled
Computing, Linguistic Data Consortium (LDC) catalog number
LDC2006S30 and ISBN 1-58563-380-1.
The Speech Controlled Computing corpus was designed to support the
development of small footprint, embedded ASR applications in the
domain of voice control for the home. It consists of the
recordings of 125 speakers of American English from four dialect
regions, three age groups and two gender groups, pronouncing
isolated words. The four primary dialect regions covered by the
corpus are North, South, West and Midland as defined by Williams
Labov's Atlas of North American English. The three primary age
groups covered by the corpus are 18-29, 30-49 and 50+.
The recordings were conducted in a sound-attenuated room at LDC
with the AKG C4000B studio condenser microphone. The
omni-directional mode of the C4000B was used. Each speaker
read a randomized word list consisting of 2,100 words (100 distinct
words appearing 21 times each). Speech utterances were digitized
and recorded to a DAT, as well as to a hard disk drive via the
Townshend DATLINK+ digital audio interface.
Speech utterances were audited as they were recorded, and any
utterances detected by the recorder that were not spoken clearly
or correctly were re-recorded. This included extraneous clicks,
coughs, sighs and breathing that may have corrupted the recorded
words. Utterances that were spoken too soft or too loud were also
re-recorded.
The digitized utterances were automatically segmented and aligned
to the word list. Then each utterance was audited and the
segmentation was checked, and corrected if necessary, by an
annotator using an auditing and segmenting tool developed by LDC.
Finally, sound files containing individual utterances were
generated using the alignment and segmentation information. The
sound files for this corpus were created with 100 msec of silent
time before and after each utterance. Any files that contained
noticeable clipping were automatically removed.
Samples
For an example of this corpus, please listen to this audio sample
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