CS 229 = = Final Project Report SPEECH & NOISE SEPARATION

A Computational Model for Multi - Instrument Music Transcription CS 229 Final Project Report , Autumn 2013

The aim of our project is to build a model for multi-instrument music transcription. Automatic music transcription is the process of converting an audio wave file into some form of music notes representations. We propose a two-step process for an automatic multiinstrument music transcription system including timbre classification and source separation using probabilistic latent component analysis.

CS 224N/229: Joint Final Project: Large-Vocabulary Continuous Speech Recognition with Linguistic Features for Deep Learning

Until this day, automated speech recognition (ASR) still remains one of the most challenging tasks in both machine learning and natural language processing. ASR research faces data with high variability, which requires highly expressive models be built. Recently, deep neural networks (DNN) have been successfully applied to various fields, including speech recognition. In this course project, We...

ARE you ? CS 229 Final Project

CS 229 Final Report: Artistic Style Transfer for Face Portraits

The goal of our project is to learn the content and style representations of face portraits, and then to combine them to produce new pictures. The content features of a face are the features that identify a face, such as the outline shape. The stylistic features are the artistic characteristics of a certain portrait or painting, such as brush strokes, or background color. We forward-pass a cont...

CS 229 Final Report : Learning to Select a Good Grasp