activity
20192022
most citedAn Interdisciplinary Review of Music Performance Analysis

43 citations · 81 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2022

SPACE: Speech-driven Portrait Animation with Controllable Expression

Siddharth Gururani, Arun Mallya, Ting-Chun Wang +2

Animating portraits using speech has received growing attention in recent years, with various creative and practical use cases. An ideal generated video should have good lip sync w…

cs.SD202143 cited

An Interdisciplinary Review of Music Performance Analysis

Alexander Lerch, Claire Arthur, Ashis Pati +1

A musical performance renders an acoustic realization of a musical score or other representation of a composition. Different performances of the same composition may vary in terms…

eess.AS20205 cited

Score-informed Networks for Music Performance Assessment

Jiawen Huang, Yun-Ning Hung, Ashis Pati +2

The assessment of music performances in most cases takes into account the underlying musical score being performed. While there have been several automatic approaches for objective…

cs.LG20204 cited

dMelodies: A Music Dataset for Disentanglement Learning

Ashis Pati, Siddharth Gururani, Alexander Lerch

Representation learning focused on disentangling the underlying factors of variation in given data has become an important area of research in machine learning. However, most of th…

eess.AS20201 cited

Visual Attention for Musical Instrument Recognition

Karn Watcharasupat, Siddharth Gururani, Alexander Lerch

In the field of music information retrieval, the task of simultaneously identifying the presence or absence of multiple musical instruments in a polyphonic recording remains a hard…

cs.SD2019

Prosody Transfer in Neural Text to Speech Using Global Pitch and Loudness Features

Siddharth Gururani, Kilol Gupta, Dhaval Shah +2

This paper presents a simple yet effective method to achieve prosody transfer from a reference speech signal to synthesized speech. The main idea is to incorporate well-known acous…