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Artwork for Our Digital Life Podcast: A series by IEEE-SPS

Our Digital Life Podcast: A series by IEEE-SPS

IEEE-SPS
Speech Recognition
Signal Processing
Machine Learning
Artificial Intelligence
Deep Learning
Medical Imaging
Neural Networks
Healthcare
Wireless Networks
Deep Neural Networks
Large Language Models
Trustworthy AI
Audio Signal Processing
Pattern Recognition
Image Processing
Educational Methods
Interdisciplinarity
Big Data
Telecommunications
6G Networks

As the world's largest professional organization, IEEE plays a significant role in enhancing the quality of our lives. Specifically, the IEEE signal processing society or SPS focuses on research and development of audio and speech processing, biomedical analysis, and wireless communication technologies, all of which are key enablers to today's modern society. In this series, we explore more about ... more

PublishesMonthlyEpisodes7Founded9 months ago
Number of ListenersCategories
PhysicsScience

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Artwork for Our Digital Life Podcast: A series by IEEE-SPS

Latest Episodes

In this episode of the IEEE Signal Processing Society podcast, Felicia Lim, a staff software engineer at Google, where she works on audio signal processing and machine learning, interviews Dr. Ivan Tashev, Partner Software Architect at Microsoft Rese... more

In this episode of the IEEE Signal Processing Society podcast, Dr. Lav Varshney, Associate Professor of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign interviews Dr. Kush Varshney, an IBM Fellow and globally recogn... more

In this episode of the IEEE Signal Processing Society podcast, Nir Shlezinger from Ben-Gurion University and Yonina C. Eldar from the Weizmann Institute of Science discuss the design of machine learning systems that are inherently efficient.

Nir Shl... more

In this episode of the IEEE Signal Processing Society podcast, Dr. Sanjeev Khudanpur, Director of the Center for Language and Speech Processing, Johns Hopkins University interviews Associate Prof. Shinji Watanabe, Language Technologies Institute, Car... more

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Recent Guests

Dr. Ivan Tashev
Partner Software Architect at Microsoft Research
Microsoft
Episode: Audio Signal Processing in the Era of AI
Kush Varshney
IBM fellow and researcher in AI governance
IBM
Episode: Trustworthy Machine Learning and Artificial Intelligence
Shinji Watanabe
Associate Professor in Language Technologies Institute
Carnegie Mellon University
Episode: The Cutting Edge of Speech Recognition
Sergios Theodoridis
Professor Emeritus for Signal Processing and Machine Learning
National and Kapodistrian University of Athens, Aalborg University, Research Institute for Big Data
Episode: Signal Processing and AI Synergies
April Khademi
Associate Professor of Biomedical, Computer, and Electrical Engineering
Toronto Metropolitan University
Episode: AI-Powered Medical Imaging

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#22
United States/Science/Physics
Apple Podcasts
#11
Germany/Science/Physics
Apple Podcasts
#44
Italy/Science/Physics
Apple Podcasts
#78
Australia/Science/Physics
Apple Podcasts
#5
Sweden/Science/Physics
Apple Podcasts
#19
Japan/Science/Physics
Apple Podcasts
#24
Brazil/Science/Physics
Apple Podcasts
#33
Israel/Science/Physics
Apple Podcasts
#42
Switzerland/Science/Physics
Apple Podcasts
#44
India/Science/Physics
Apple Podcasts
#75
Spain/Science/Physics
Apple Podcasts
#129
Sweden/Science

Talking Points

Recent interactions between the hosts and their guests.

The Cutting Edge of Speech Recognition
Q: Where do you see the future of speech recognition going?
I think multi-modality becomes more important and we should focus on understanding entire human conversations.
The Cutting Edge of Speech Recognition
Q: What do you think are driving these improvements?
It's a combination of increased data quality, improved computing resources, and open-source knowledge sharing.
Signal Processing and AI Synergies
Q: What do you think is going to be the next big innovation for all of these AI and ML?
Novelty is unpredictable, but it seems large language models and generative models will continue to thrive, with the possibility of a comeback for recurrent neural networks.
Signal Processing and AI Synergies
Q: What is the place of collaboration in achieving all these innovations that we have? Is interdisciplinary work something that you had experience or by excessive career?
Interdisciplinary collaboration is crucial today due to the complexity of technology which requires knowledge from various fields to meet societal demands.
Signal Processing and AI Synergies
Q: Could you discuss with us a specific project where machine learning is significant to improve outcomes of signal processing?
It's difficult to pick just a simple discipline, but speech and audio recognition, as well as image processing, serve as prominent examples where machine learning has made significant advances.

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Frequently Asked Questions About This Podcast

What is This Podcast about and what kind of topics does it cover?

This series explores the advancements and research surrounding signal processing, emphasizing its pivotal role in audio, speech processing, biomedical analysis, and wireless communication technologies. Experts from various institutions frequently share insights into complex topics such as machine learning applications in signal processing, the evolution of speech recognition technologies, and the integration of artificial intelligence within communications. The content features discussions that blend theoretical concepts with practical applications, making it particularly valuable for professionals and enthusiasts looking to understand the latest developments in these critical fields.

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1. Hidden Brain

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this podcast launched 9 months ago and published 7 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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Recent guests on this podcast include:

1. Dr. Ivan Tashev
2. Kush Varshney
3. Shinji Watanabe
4. Sergios Theodoridis
5. April Khademi

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