Our Digital Life Podcast: A series by IEEE-SPS
Our Digital Life Podcast: A series by IEEE-SPS
Podcast Description
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 the works of signal processing and engage with various global speakers.
Podcast Insights
Content Themes
The podcast centers around themes of audio and speech processing, biomedical analysis, and advancements in wireless communication technologies. Specific episodes delve into topics like AI-driven methods in medical imaging, with featured discussions on how innovations improve diagnostic accuracy and therapeutic approaches, as well as challenges in data constraints and solutions like FDA-approved imaging algorithms.
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 the works of signal processing and engage with various global speakers.
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, Carnegie Mellon University. They talk about the latest research and innovations in speech recognition technologies and their impact across various industries.
Shinji Watanabe
Shinji Watanabe is an Associate Professor at Carnegie Mellon University in Pittsburgh and a leading researcher in speech and language processing. His work spans automatic speech recognition, speech enhancement, spoken language understanding, and machine learning for speech and language processing. He has contributed more than 500 publications to peer-reviewed journals and received several awards, including the best paper award from ISCA Interspeech 2024.
In this episode, Associate Prof. Watanabe reflects on the transformative progress in speech recognition over the past decade, highlighting milestones from the adoption of deep neural networks to the rise of large-scale models like OpenAI Whisper. He discusses the ongoing challenges in achieving human-level understanding in complex scenarios such as multi-speaker conversations, accented and multilingual speech, and child or disordered speech. He concludes with thoughts on academia’s enduring role in shaping the field, and how his inspiration is often drawn from science fiction and Japanese animation.
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