1. A method comprising: requesting, via a processor, a respective transcription response associated with transcribing input speech, the respective transcription response being from each of a plurality of networked entities, wherein at least one entity of the plurality of networked entities comprises an automatic labeler that transcribes the input speech as its respective transcription response and at least one entity of the plurality of networked entities comprises a human crowd worker who transcribes the input speech as its respective transcription response; receiving, from each of the plurality of networked entities, the respective transcription response and, for a transcription response received from the human crowd worker, a number of times the respective human crowd worker listened to the input speech to provide the respective transcription response; determining a maximum number of transcription responses to receive from the plurality of networked entities; calculating, via the processor and using a regression model, an accuracy threshold for the transcription responses, wherein the accuracy threshold: (1) requires a number of matching responses among the transcription responses; (2) is based on a time of day when each of the transcription responses is received; and (3) is based on a number of times the respective human crowd worker listened to the input speech; incrementally receiving the transcription responses from the plurality of networked entities until one of the accuracy threshold is reached and the maximum number of transcription responses is received; and generating, via the processor, an output response to the input speech from the number of matching transcription responses, wherein the output response is a recognition candidate or a transcription of the input speech.