5 papers · 1 filter
DART: Disentanglement of Accent and Speaker Representation in Multispeaker Text-to-Speech
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
Recent advancements in Text-to-Speech (TTS) systems have enabled the generation of natural and expressive speech from textual input. Accented TTS aims to enhance user experience by…
Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
With rapid globalization, the need to build inclusive and representative speech technology cannot be overstated. Accent is an important aspect of speech that needs to be taken into…
Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
Accent plays a significant role in speech communication, influencing one's capability to understand as well as conveying a person's identity. This paper introduces a novel and effi…
MidiCaps: A large-scale MIDI dataset with text captions
Jan Melechovsky, Abhinaba Roy, Dorien Herremans
Generative models guided by text prompts are increasingly becoming more popular. However, no text-to-MIDI models currently exist due to the lack of a captioned MIDI dataset. This w…
Mustango: Toward Controllable Text-to-Music Generation
Jan Melechovsky, Zixun Guo, Deepanway Ghosal +3
The quality of the text-to-music models has reached new heights due to recent advancements in diffusion models. The controllability of various musical aspects, however, has barely…