From the 2 of 30 linked papers with an AI index.
6 papers · 1 filter
Dissecting Sensitivity to Training Language in Self-Supervised Speech Learning Using Neural Audio Codec Tokens
Daigo Takizawa, Tomohiko Nakamura, Samuele Cornell +3
The paper investigates how the language used to train neural audio codecs and self‑supervised speech models affects performance, finding that codec training language has little imp…
OpenBEATs: A Fully Open-Source General-Purpose Audio Encoder
Shikhar Bharadwaj, Samuele Cornell, Kwanghee Choi +4
OpenBEATs is an open-source framework that extends the BEATs audio encoder with multi-domain masked-token pretraining, achieving state-of-the-art results on a wide range of audio t…
Modeling Overlapped Speech with Shuffles
Matthew Wiesner, Samuele Cornell, Alexander Polok +3
We propose to model parallel streams of data, such as overlapped speech, using shuffles. Specifically, this paper shows how the shuffle product and partial order finite-state autom…
UrgentMOS: Unified Multi-Metric and Preference Learning for Robust Speech Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li +12
Automatic speech quality assessment has become increasingly important as modern speech generation systems continue to advance, while human listening tests remain costly, time-consu…
The CMU-AIST submission for the ICME 2025 Audio Encoder Challenge
Shikhar Bharadwaj, Samuele Cornell, Kwanghee Choi +4
This technical report describes our submission to the ICME 2025 audio encoder challenge. Our submitted system is built on BEATs, a masked speech token prediction based audio encode…
ARECHO: Autoregressive Evaluation via Chain-Based Hypothesis Optimization for Speech Multi-Metric Estimation
Jiatong Shi, Yifan Cheng, Bo-Hao Su +6
Speech signal analysis poses significant challenges, particularly in tasks such as speech quality evaluation and profiling, where the goal is to predict multiple perceptual and obj…