ألف مقطع عربي

#SamsungAIForum

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#SAIT(Samsung Advanced Institute of Technology): http://smsng.co/sait

People play a central role in the machine learning life cycle. Consequently, building machine learning systems that are reliable, trustworthy, and fair requires that relevant stakeholders—including developers, users, and the people affected by these systems—have at least a basic understanding of how they work. Yet what makes a system “intelligible” is difficult to pin down. Intelligibility is a fundamentally human-centered concept that lacks a one-size-fits-all solution. I will explore the importance of evaluating methods for achieving intelligibility in context with relevant stakeholders, ways of empirically testing whether intelligibility techniques achieve their goals, and why we should expand our concept of intelligibility beyond machine learning models to other aspects of machine learning systems, such as datasets and performance metrics.

#SAIF #SamsungAIForum

For more info, visit our page:
#SAIT(Samsung Advanced Institute of Technology): http://smsng.co/sait

End-to-end models allow us to represent the entire speech recognition pipeline (i.e., conventional acoustic, pronunciation and language models) by one neural network. This has huge implications for privacy, reliability and latency. In this talk, we will discuss the research developments around E2E models that have allowed it to reach the accuracy of conventional models, at a fraction of the model size and reduced latency. In addition, we will present further benefits of these models with respect to multi-lingual speech recognition.

#SAIF #SamsungAIForum

For more info, visit our page:
#SAIT(Samsung Advanced Institute of Technology): http://smsng.co/sait