Automatic Music Composition

Generate music compositions automatically in a musically plausible way.

Skeleton Plays Piano: Generating Pianist Movement from MIDI Data

We train a model to take the input of MIDI data, and output the visual performance as expressive body movements for pianist. It can be used for demonstration purpose for music learners, or immersive music enjoyment system, or human-computer interactions in automatic accompaniment systems. We show all the demo videos of the generated visual performance (as skeleton key points) compared with real human on same pieces.

Piano Music Transcription Into Music Notation

A complete piano music transcription system from transcribing notes from audio waveform to arranging as readable score notations

Creating A Musical Performance Dataset For Multimodal Music Analysis

We create an audio-visual, multi-track, and multi-instrument music performance dataset that comprises a number of chamber music assembled from coordinated but separately recorded performances of individual tracks. With ground-truth pitch/note annotations and clean individual audio tracks available, this can be used for multi-modal analysis of music performance.

Score Following For Expressive Piano Performance

We address the "sustained effect" in piano music performance, caused by the usage of sustained pedal or legato articulations. Due to this effect, the mixture of energy between the sustained and following notes (non-notated in the score) always results in delay erros in score following systems. We propose to modify the audio feature representations to reduce the sustained effect and enhance the robustness of score following systems.

Automatic Lyrics Display For A Live Chorus Performance

Live musical performances (e.g., choruses, concerts, and operas) often require the display of lyrics for the convenience of the audience. We propose a computational system to automate this real-time lyrics display process using signal processing techniques

Audio-visual Analysis of Music Performance

We propose to leverage visual information captured from music performance videos to advance several music information retrieval (MIR) tasks, such as source association, multi-pitch analysis, and vibrato analysis.


End-to-End Generation of Talking Faces from Noisy Speech

We propose a system that can generate talking faces from input noisy speech and a reference image.

Adversarial Training for Speech Super-Resolution

We propose an adversarial training method for speech super-resolution or speech bandwidth extension.

Audio-Visual Speech Source Separation

we propose an audio-visual Audio-Visual Deep Clustering model (AVDC) to integrate visual information into the process of learning better feature representations (embeddings) for Time-Frequency (T-F) bin clustering.

Generating 3D Talking Face Landmarks from Speech

We propose to use a Convolutional network to generate 3D landmarks of a talking face from acoustic speech waveform.

Generating Talking Face Landmarks from Speech

We propose to use a LSTM network to generate landmarks of a talking face from acoustic speech.

General Sounds

Sound Search By Vocal Imitation

We propose to make general audio databases content-searchable using vocal imitation of the desired sound as the query key: A user vocalizes the audio concept in mind and the system retrieves audio recordings that are similar, in some way, to the vocalization.


Prior Projects