6 papers
On the Effect of Segmentation Width and Cluster Size on Speech Resynthesis and Continuation in Generative Spoken Language Models
Shunsuke Kando, Wataru Nakata, Shinnosuke Takamichi +1
Generative Spoken Language Modeling (GSLM) enables text-free speech modeling by training language models (LMs) using discrete speech representations instead of textual transcriptio…
How Much Do Large Language Models Know about Human Motion? A Case Study in 3D Avatar Control
Kunhang Li, Jason Naradowsky, Yansong Feng +1
We explore the human motion knowledge of Large Language Models (LLMs) through 3D avatar control. Given a motion instruction, we prompt LLMs to first generate a high-level movement…
Do Self-Supervised Speech Models Exhibit the Critical Period Effects in Language Acquisition?
Yurie Koga, Shunsuke Kando, Yusuke Miyao
This paper investigates whether the Critical Period (CP) effects in human language acquisition are observed in self-supervised speech models (S3Ms). CP effects refer to greater dif…
Tracking World States with Language Models: State-Based Evaluation Using Chess
Romain Harang, Jason Naradowsky, Yaswitha Gujju +1
Large Language Models (LLMs) exhibit emergent capabilities in structured domains, suggesting they may implicitly internalize high-fidelity representations of world models. While pr…
Exploring the Effect of Segmentation and Vocabulary Size on Speech Tokenization for Speech Language Models
Shunsuke Kando, Yusuke Miyao, Shinnosuke Takamichi
The purpose of speech tokenization is to transform a speech signal into a sequence of discrete representations, serving as the foundation for speech language models (SLMs). While s…
Does it Chug? Towards a Data-Driven Understanding of Guitar Tone Description
Pratik Sutar, Jason Naradowsky, Yusuke Miyao
Natural language is commonly used to describe instrument timbre, such as a "warm" or "heavy" sound. As these descriptors are based on human perception, there can be disagreement ov…