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The emergence of deep learning and big data lectures requires teachers and students to adopt HPC as an integral part of their knowledge domain.
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"You cannot run a $400 million company without data," lectured Mr. Turan, the president of the Nassau Health Care Corporation, the public benefit corporation that runs the Nassau University Medical Center, seven clinics and the A. Holly Patterson nursing home.
He presented fraudulent data in lectures and in published papers, and he used this data to obtain millions of dollars in federal grants from the National Institutes of Health — a crime subject to as many as five years in federal prison.
Expecting that students can apply these skills (or at least follow their application), instructors present graphical data in lecture to support their course content, ask students to calculate and understand probabilities for basic genetics problems, and otherwise rely on their students' assumed quantitative skill set.
The performance of the ASR system trained on lecture data and tested on lecture data is slightly poorer than the ASR system trained on Olive data and tested on Olive data.
The reason could be that there is relatively more uniformity in the Olive data (read speech) compared to lecture speech.
The response to this survey was reasonable, with the third year student response being attenuated by poor attendance at the data-collection lecture (although over 90% of the third year students who attended the lecture completed the questionnaire).
Table 3 shows the word error rates (WERs) and phone error rates (PERs) given by the ASR systems trained on the Olive and lecture data and tested on the Olive and lecture data (TTS data), respectively.
More than 4,300 abstracts from research groups around the world were presented during the 4-day programme, including original data and outstanding lectures based on the most recent literature.
The performance gap between the ASR system trained on lecture data and LibriSpeech is big as compared to that between the ASR system trained on Olive and LibriSpeech data because LibriSpeech is a read speech corpus just like Olive, while lecture data is spontaneous data.
Note, for computing WERs for both the Olive and lecture data, we respectively used the word-level transcriptions available at the Project Gutenberg website and those available at Coursera, as reference transcriptions.
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