88 citations · 145 across the 54 of their papers we have counts for
13 papers · 1 filter
Language-Statistical Analysis of Neural Audio Codec Tokens Across Architectures, Corpora, and Noise Conditions
Joonyong Park, Shinnosuke Takamichi, David M. Chan +3
Neural audio codecs (NACs) convert speech into discrete token sequences, and prior work has reported that these sequences follow language-like statistical laws. This paper analyzes…
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…
Low-Latency Real-Time Audio Game Commentary System via LLM-Based Parallel Text Generation
Ryota Kawamatsu, Anum Afzal, Yuki Saito +5
We present a low-latency real-time audio game commentary system that generates spoken commentary directly from live gameplay video. In this end-to-end setting, a key bottleneck is…
Real-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approaches
Anum Afzal, Yuki Saito, Hiroya Takamura +5
Real-time video commentary generation provides textual descriptions of ongoing events in videos. It supports accessibility and engagement in domains such as sports, esports, and li…
Analysing the Language of Neural Audio Codecs
Joonyong Park, Shinnosuke Takamichi, David M. Chan +3
This study presents a comparative analysis of the statistical and linguistic properties of neural audio codecs (NACs). We investigate discrete speech tokens produced by various NAC…
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…