April-Event2021 (5)

Overview

Are you an audio or speech processing engineer working on product development or DSP algorithms and looking to integrate AI capabilities within your projects?

In this session you will learn the basics of deep learning for audio applications by walking through a detailed example of speech classification, entirely based on MATLAB code. We will cover creating and accessing labeled data, using time-frequency transformations, extracting features, designing and training deep neural network architectures, and testing prototypes on real-time audio.

We will also discuss interoperability with other popular deep learning tools, including exploiting available pre-trained network.

audio-toolbox-ml-and-dl-augment-synthesize-audio-speech-datasets

Highlights:

  • Acquiring, segmenting and labeling audio recordings and ingesting existing datasets
  • Extracting standard speech and audio features and using 2D time-frequency representations
  • Designing and analyzing deep networks and exchanging models with other popular frameworks (e.g. via ONNX)
  • Accelerating computations using GPUs and prototyping trained models on real-world signals

 

Register Today!

Speaker

Siti Safwana


Siti Safwana is an Application Engineer at TechSource Systems. She is specialized in the field of image processing, computer vision, machine learning, and deep learning with MATLAB. She helps various customers across different industries on projects such as real-time object recognition, manufacturing defect objects detection using Deep Learning and Computer Vision, data forecasting analytics, and multiple image processing project-based.
She additionally holds an HRDF Train-The-Trainer (TTT) certificate and trained in official MathWorks training programs like MATLAB Fundamental, Image Processing, and Machine Learning. She teaches and covers ASEAN region such as Malaysia and Philippines.
Siti Safwana holds an M.Eng in Science in Electronics from Universiti Teknikal Malaysia Melaka (UTeM) and currently pursuing her Ph.D. in Science in Electronic researching computer vision field in the domain of depth/disparity map and 3D reconstruction using Artificial Intelligence at UTeM under the department of Faculty of Electronic and Computer Engineering.

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