" the current and future potential of music technology is both exciting and imperative for its cross-disciplinary applications "


Machine Learning Research Projects at the Georgia Institute of Technology (2020-2022)

  1. Master's Project (2021 - Present)

    • Collaborators: Alison Ma

    • Description: Details will be added soon.

  2. Phoneme Sequence Modeling for Speech (2021)

    • Collaborators: Nikhil Ravi Krishnan, Akhil Shukla, Alison Ma

    • Description: Worked with HMMGMMs, and BiLSTM-CTC Networks using the TIMIT dataset

  3. Audio versus MIDI-based Genre Classification (2021)

    • Collaborators: Alison Ma

    • Description: Conducted ablation study experiments on the LAKH MIDI Dataset v0.1, Million Song Dataset, and top- MAGD MSD Allmusic Genre Dataset to compare MIDI and audio-based classification with Random Forest, MLP, and CNN architectures

  4. Deep Learning Approaches to Symbolic Sequential Music Generation and Musical In-painting (2021)​
    • Collaborators: Yilun Zha, Alison Ma, Iman Haque, Yufei Xu, Bowen Ran

    • Description: Surveyed deep learning approaches to symbolic sequential music generation and musical in-painting for ABC format, employing LSTMs with attention and Transformer architectures on the folk-rnn data_v2_worepeats dataset

  5. Automated Image Captioning (2020)

    • Collaborators: Aryan Pariani, Ishaan Mehra, Alison Ma, Jun Chen, Max Rivera

    • Description: Utilized attention-based Mask-RCNNs and LSTMs on the Flickr30k Kaggle dataset to achieve a BLEU score of 0.795 on the best caption from the test set in Keras

  6. The Relationship Between Stem Combinations of Features and Popularity through the 1925-2010s (2020)

    • Collaborators: Alison Ma

    • Description: Executed a feature analysis study and conducted statistical analysis utilizing Billboard Hot 100 metadata and SigSep Open-UnMix extracted audio stems for songs in the Million Song Dataset

Max for Live Human-Computer Interaction

Google Chrome Speech-to-Text Performance System (2019)

Collaborators: Alison Ma

Description: Designed a real-time performance system using JavaScript, node.js, and socket.io to integrate Google Chrome's Speech-to-Text engine with Max for Live devices at the Berklee College of Music

Max for Live OSC Phone Sensor MIDI Mapper (2021)

Collaborators: Joshua Williams, Alison Ma

Description: Co-developed MaxMSP and Max for Live real-time panning tools for performers for use with Ableton Live and Audinate Dante at the Berklee College of Music Digital Forest Multimedia Installation

Collaborators: Alison Ma

Description: MultiSense OSC application, MIDI mapping in Max for Live.

Musical Map: Location & Weather Sonification (2021)

Collaborators: Nathan Johnson, Kelian Li, Alison Ma

Description: Max For Live MIDI mapping and generative music, JavaScript and websockets.

ml.lib Sound Synthesis (2021)

Collaborators: Alison Ma

Description: ml.lib mappings for sound synthesis.

10.2 OSC Surround Sound Panner (2019)