5 papers
Multichannel Audio Quality Assessment: Extending Pretrained Perceptual Models to Spatial Audio
Gouthaman KV, Shiv Gehlot, Vishnu Raj +2
Accurate perceptual quality assessment is essential for evaluating and optimizing spatial audio, where perceived quality depends on both signal fidelity and inter-channel spatial r…
DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning
Batuhan K. Karaman, Aditya Rawal, Suhaila Shakiah +4
Reinforcement learning with verifiable rewards has emerged as a promising paradigm for enhancing the reasoning capabilities of large language models particularly in mathematics. Cu…
Enhanced Generative Machine Listener
Vishnu Raj, Gouthaman KV, Shiv Gehlot +2
We present GMLv2, a reference-based model designed for the prediction of subjective audio quality as measured by MUSHRA scores. GMLv2 introduces a Beta distribution-based loss to m…
Towards Evaluating Generative Audio: Insights from Neural Audio Codec Embedding Distances
Arijit Biswas, Lars Villemoes
Neural audio codecs (NACs) achieve low-bitrate compression by learning compact audio representations, which can also serve as features for perceptual quality evaluation. We introdu…
Attentive AV-FusionNet: Audio-Visual Quality Prediction with Hybrid Attention
Ina Salaj, Arijit Biswas
We introduce a novel deep learning-based audio-visual quality (AVQ) prediction model that leverages internal features from state-of-the-art unimodal predictors. Unlike prior approa…