June 2019
Intermediate to advanced
308 pages
7h 21m
English
Content preview from Hands-On Deep Learning for IoT
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Collecting data
Data collection for ASR is a challenging task for many reasons, including privacy. Consequently, open source datasets are limited in number. Importantly, these datasets may not be easy to access, may have insufficient data/speakers, or may be noisy. In this context, we decided to use two different datasets for the two use cases. For the voice-driven controlled smart light, we are using Google’s speech command datasets, and for use case two, we can scrap data from one of three popular open data sources, LibriVox, LibriSpeech ASR, corpus, voxceleb, and YouTube.
Google's speech command dataset includes 65,000 one-second long utterances of 30 short words, contributed to by thousands of different members of the public through the ...
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