10 citations · 15 across the 18 of their papers we have counts for
6 papers · 1 filter
TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization
Chia-Yu Hung, Navonil Majumder, Zhifeng Kong +6
We introduce TangoFlux, an efficient Text-to-Audio (TTA) generative model with 515M parameters, capable of generating up to 30 seconds of 44.1kHz audio in just 3.7 seconds on a sin…
ETTA: Elucidating the Design Space of Text-to-Audio Models
Sang-gil Lee, Zhifeng Kong, Arushi Goel +3
Recent years have seen significant progress in Text-To-Audio (TTA) synthesis, enabling users to enrich their creative workflows with synthetic audio generated from natural language…
Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data
Sreyan Ghosh, Sonal Kumar, Zhifeng Kong +3
We present Synthio, a novel approach for augmenting small-scale audio classification datasets with synthetic data. Our goal is to improve audio classification accuracy with limited…
Improving Text-To-Audio Models with Synthetic Captions
Zhifeng Kong, Sang-gil Lee, Deepanway Ghosal +5
It is an open challenge to obtain high quality training data, especially captions, for text-to-audio models. Although prior methods have leveraged \textit{text-only language models…
Audio Dialogues: Dialogues dataset for audio and music understanding
Arushi Goel, Zhifeng Kong, Rafael Valle +1
Existing datasets for audio understanding primarily focus on single-turn interactions (i.e. audio captioning, audio question answering) for describing audio in natural language, th…
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Zhifeng Kong, Arushi Goel, Rohan Badlani +3
Augmenting large language models (LLMs) to understand audio -- including non-speech sounds and non-verbal speech -- is critically important for diverse real-world applications of L…