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20192024
most citedAcoustic Modeling for Automatic Lyrics-to-Audio Alignment

5 citations · 7 across the 5 of their papers we have counts for

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eess.AS2024

MorphFader: Enabling Fine-grained Controllable Morphing with Text-to-Audio Models

Purnima Kamath, Chitralekha Gupta, Suranga Nanayakkara

Sound morphing is the process of gradually and smoothly transforming one sound into another to generate novel and perceptually hybrid sounds that simultaneously resemble both. Rece…

eess.AS2023

Example-Based Framework for Perceptually Guided Audio Texture Generation

Purnima Kamath, Chitralekha Gupta, Lonce Wyse +1

Controllable generation using StyleGANs is usually achieved by training the model using labeled data. For audio textures, however, there is currently a lack of large semantically l…

eess.AS2022

Music-robust Automatic Lyrics Transcription of Polyphonic Music

Xiaoxue Gao, Chitralekha Gupta, Haizhou Li

Lyrics transcription of polyphonic music is challenging because singing vocals are corrupted by the background music. To improve the robustness of lyrics transcription to the backg…

eess.AS20192 cited

Automatic Lyrics Alignment and Transcription in Polyphonic Music: Does Background Music Help?

Chitralekha Gupta, Emre Yılmaz, Haizhou Li

Background music affects lyrics intelligibility of singing vocals in a music piece. Automatic lyrics alignment and transcription in polyphonic music are challenging tasks because t…

eess.AS20195 cited

Acoustic Modeling for Automatic Lyrics-to-Audio Alignment

Chitralekha Gupta, Emre Yılmaz, Haizhou Li

Automatic lyrics to polyphonic audio alignment is a challenging task not only because the vocals are corrupted by background music, but also there is a lack of annotated polyphonic…