Abstract:
A mechanism is provided for utilizing content analytics to automate corrections and improve speech recognition accuracy. A set of current corrected content elements is identified within a transcribed corrected media. Each current corrected content element in the set of current corrected content elements is weighted with an assigned weight based on one or more predetermined weighting conditions and a context of the transcribed corrected media. A confidence level is associated with each corrected content element based on the assigned weight. The set of current corrected content elements and the confidence level associated with each current corrected content element in a set of corrected elements is stored in a storage device for use in a subsequent transcription correction.
Abstract:
A mechanism is provided for subtractive transcript improvement. The mechanism identifies a set of corrections made to a previous transcript, where the set of corrections comprise, for each correction in the set of corrections, an erred phrase and a correction made to the erred phrase. For each erred phrase in a set of erred phrases in a current transcript, the mechanism determines whether the erred phrase in the current transcript matches an erred phrase in the set of corrections made to the previous transcript. Responsive to the erred phrase in the current transcript matching an erred phrase in the set of corrections made to the previous transcript, the mechanism corrects the erred phrase in the current transcript with the correction made to the erred phrase in the previous transcript.
Abstract:
Embodiments relate to determining the health of a network community. Aspects include defining, via a computer processor, measurable aspects associated with the network community. The measurable aspects include metrics for one or more of: quantified interactions among users in the network community, quantified activities among the users that are associated with a topic, and quantified activities indicative of network community accessibility. Aspects also include monitoring activities conducted via the network community, collecting data from monitored activities that correspond to the measurable aspects, and analyzing collected data from the monitored activities. The analyzing is performed as a function of the metrics. Aspects further include determining, via the computer processor, a health status of the network community from results of the analyzing.