The Sound of AI – Challenges & Solutions in Speech & Audio
Founder & Machine Learning at Up·AI
The Sound of AI – Challenges & Solutions in Speech & Audio
Founder & Machine Learning at Up·AI
Orian is the cofounder of Up·AI, a consultancy of two specialists focusing on hands-on speech and audio machine learning projects. Up·AI ‘s most well-known collaborator is Waves Audio Ltd., with whom they are working on dubbing related pro-audio algorithms. Additionally Up·AI is part of the HarmonAI community, working on generative audio tools as part of Stability Ai.
Orian specializes in the intersection of academic research and industry end-to-end ML development. Orian’s passion for machine learning is rooted in a Master’s degree in Computational Cognition, where Orian researched and mathematically modeled human behavior.
Orian is the cofounder of Up·AI, a consultancy of two specialists focusing on hands-on speech and audio machine learning projects. Up·AI ‘s most well-known collaborator is Waves Audio Ltd., with whom they are working on dubbing related pro-audio algorithms. Additionally Up·AI is part of the HarmonAI community, working on generative audio tools as part of Stability Ai.
Orian specializes in the intersection of academic research and industry end-to-end ML development. Orian’s passion for machine learning is rooted in a Master’s degree in Computational Cognition, where Orian researched and mathematically modeled human behavior.
Audio representation methods are becoming more varied and rich with each day. The possibilities are endless and so are the different challenges they can solve. Text based or textless, DSP feature selection or raw WAV? How bounded are we by available datasets and do we have to use our own ears to test the results for naturalness?
The methods for representing audio have evolved over time. From Mel spectrograms, gammatone filters and wavelet transforms to the latest state-of-the-art
transformers models (including wav2vec2, hubert, etc.). Each method has its pros and cons. In this round table discussion, we will review a few of these methods. We will then turn to the application side and see how audio representations are used in different tasks.
Discussion of real life applications will be encouraged, so to learn of the challenges of moving from the research domain to practical usage. We will follow-up with a discussion of different methods for computing audio similarities and audio generation.
Audio representation methods are becoming more varied and rich with each day. The possibilities are endless and so are the different challenges they can solve. Text based or textless, DSP feature selection or raw WAV? How bounded are we by available datasets and do we have to use our own ears to test the results for naturalness?
The methods for representing audio have evolved over time. From Mel spectrograms, gammatone filters and wavelet transforms to the latest state-of-the-art
transformers models (including wav2vec2, hubert, etc.). Each method has its pros and cons. In this round table discussion, we will review a few of these methods. We will then turn to the application side and see how audio representations are used in different tasks.
Discussion of real life applications will be encouraged, so to learn of the challenges of moving from the research domain to practical usage. We will follow-up with a discussion of different methods for computing audio similarities and audio generation.
| 8:45 | Reception |
|---|---|
| 9:30 | Opening words by WiDS TLV ambassador Nitzan Gado and by Lily Ben Ami, CEO of the Michal Sela Forum |
| 9:50 | Prof. Bracha Shapira – Data Challenges in Recommender Systems Research: Insights from Bundle Recommendation |
| 10:20 | Juan Liu – Accounting Automation: Making Accounting Easier So That People Can Forget About It |
| 10:50 | Break |
| 11:00 | Lightning talks |
| 12:20 | Lunch & poster session |
|---|---|
| 13:20 | Roundtable session & poster session |
| 14:05 | Roundtable closure |
| 14:20 | Break |
| 14:30 | Merav Mofaz – “Every Breath You Take and Every Move You Make…I'll Be Watching You:” The Sensitive Side of Smartwatches |
| 14:50 | Reut Yaniv – Ad Serving in the Online Geo Space Along Routes |
| 15:10 | Rachel Wities - It’s Not Just the Doctor’s Handwriting: Challenges and Opportunities in Healthcare NLP |
| 15:30 | Closing remarks |
| 15:40 | End |
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