4 papers
ParaSpeechCLAP: A Dual-Encoder Speech-Text Model for Rich Stylistic Language-Audio Pretraining
Anuj Diwan, Eunsol Choi, David Harwath
We introduce ParaSpeechCLAP, a family of dual-encoder models that map speech and text style captions into a shared embedding space, supporting rich intrinsic (speaker-level) and si…
Scaling Rich Style-Prompted Text-to-Speech Datasets
Anuj Diwan, Zhisheng Zheng, David Harwath +1
We introduce Paralinguistic Speech Captions (ParaSpeechCaps), a large-scale dataset that annotates speech utterances with rich style captions. While rich abstract tags (e.g. guttur…
Rhapsody: A Dataset for Highlight Detection in Podcasts
Younghan Park, Anuj Diwan, David Harwath +1
Podcasts have become daily companions for half a billion users. Given the enormous amount of podcast content available, highlights provide a valuable signal that helps viewers get…
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma +3
Spatial sound reasoning is a fundamental human skill, enabling us to navigate and interpret our surroundings based on sound. In this paper we present BAT, which combines the spatia…