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cs.SD2025

FoleyBench: A Benchmark For Video-to-Audio Models

Satvik Dixit, Koichi Saito, Zhi Zhong +2

Video-to-audio generation (V2A) is of increasing importance in domains such as film post-production, AR/VR, and sound design, particularly for the creation of Foley sound effects s…

cs.SD2025

Learning Perceptually Relevant Temporal Envelope Morphing

Satvik Dixit, Sungjoon Park, Chris Donahue +1

Temporal envelope morphing, the process of interpolating between the amplitude dynamics of two audio signals, is an emerging problem in generative audio systems that lacks sufficie…

cs.SD2025

Mellow: a small audio language model for reasoning

Soham Deshmukh, Satvik Dixit, Rita Singh +1

Multimodal Audio-Language Models (ALMs) can understand and reason over both audio and text. Typically, reasoning performance correlates with model size, with the best results achie…

cs.SD2024

Vision Language Models Are Few-Shot Audio Spectrogram Classifiers

Satvik Dixit, Laurie M. Heller, Chris Donahue

We demonstrate that vision language models (VLMs) are capable of recognizing the content in audio recordings when given corresponding spectrogram images. Specifically, we instruct…

cs.SD2024

MACE: Leveraging Audio for Evaluating Audio Captioning Systems

Satvik Dixit, Soham Deshmukh, Bhiksha Raj

The Automated Audio Captioning (AAC) task aims to describe an audio signal using natural language. To evaluate machine-generated captions, the metrics should take into account audi…

cs.SD2024

Improving Speaker Representations Using Contrastive Losses on Multi-scale Features

Satvik Dixit, Massa Baali, Rita Singh +1

Speaker verification systems have seen significant advancements with the introduction of Multi-scale Feature Aggregation (MFA) architectures, such as MFA-Conformer and ECAPA-TDNN.…