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Wen-Chuan Chen

Education

National Tsing Hua University, Master of Science, Power Mechanical Engineering, 2017 ~ 2019

  • Division of Electrical Control, GPA: 4.17
  • Telecom Electro-Acoustic Audio Lab directed by Dr. Mingsian R. Bai
  • Master's Thesis: "Deep Learning Applied to Speech and Audio Signal Processing under Adverse Environments"

University@2x

National Sun Yat-sen university, Bachelor of Science, Mechanical and Electro-mechanical Engineering, 2013 ~ 2017

University@2x

Skills


Programming

  • Python (Tensorflow/Pytorch)
  • C / C++ (STL)
  • OpenCV
  • Git


Computer Science

  • Machine / Deep Learning 
  • Computer Vision 
  • Self-driving cars
  • Data Structure and Algorithms


Signal Processing

  • Digital Signal Processing
  • Digital Image Processing
  • Acoustic Array Signal Processing
  • Music Information Retrieval

Publication

[Journal] "Multichannel Sound Event Separation and Detection in Adverse Environments Using Convolutional Recurrent Neural Network with Complex Masking," The Journal of the Acoustical Society of America.

Propose an end-to-end polyphonic sound event separation and detection system aimed at separating and detecting multiple sound events. The system consists of a convolutional recurrent neural network in conjunction with an ideal complex mask. In addition, a discriminative training network is employed to increase the robustness.

[Conference] "Deep Learning Applied to Dereverberation and Sound Event Classification," International Congress on Acoustics, SEPT. 09-13, 2019 in Germany.

Investigates dereverberation and sound event detection techniques, with the aid of deep learning. The proposed system consists of two units: a multichannel deep neural front-end and a VGG-like classifier back-end trained with generic data augmented by various room impulse responses.

[Conference] "Robotic Voice Assistant Equipped with Binaural Audio," INTERNOISE, JUNE. 16-19, 2019 in Madrid.

The robot is comprised primarily of three functional units: (1) a microphone array used to locate the user position (2) a cloud-based DNN-based classifier for command words recognition (3) loudspeaker array for binaural audio sound effect.

Side Projects

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Audio/Speech Separation

Source separation, blind signal separation (BSS) or blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process.

 My Implementation on Github

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Panorama Stitching 

Automatic panorama stitching technology has been widely adopted in many applications such as Google Street View, panorama photos on smartphones, and stitching software such as Photosynth and AutoStitch.

 My Implementation on Github

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