DeepWave - About

About DeepWave

DeepWave was established through Taiwan Germination Program in September 2019 by Professor Roger Chang from Department of Computer Science & Information Engineering, National Taiwan University; CTO, Ken Yeh and CEO, Henry Lin. DeepWave goals to create accessible and affordable AI application tools in audio processing for everyone. We are specialized in applying AI algorithm model in audio signal recognition, retrieval and analysis. For over two decades, our key members have dived in to related fields and won numerous prestigious international audio & music analysis competitions. We currently have 20+ types of audio-related algorithm ready for use, which has applied to music entertainment, online education, content and new media, and smart manufacturing. With a clear roadmap and strategy, We hope to filling the gap in the competent audio signal processing tools and services which lack of flexibility and costly in market.

Chief Scientist Officer

Dr. Roger Chang has nearly 30 years’ research and industry experience in machine learning in acoustics. He earned his doctorate from UC Berkeley in 1992 and pursues his career in-depth for what he learned about back to Taiwan. With his achievement in MathWorks, Dr. Roger Chang inheriting his knowledge among students in National Tsinghua University and National Taiwan University. When the time has come, Dr. Roger Chang and his student, Ken Yeh, decided to start a business - DeepWave in 2019. DeepWave provides substantial solutions in audio signal processing targeting to whom needed implementing AI applications to their industry in order to achieve digital transformation.

Meet our team

DeepWave is a group of music-loving engineers who extend their passion and profession to audio processing. Our team composition fully covered in front and back-ends, AI, product management and business development. We might be tiny but rather than smart that can jointly implement products and projects perfectly. We know how the music AI's working principle, training process and operation, which can reduce trial and error.