1 citations · 1 across the 11 of their papers we have counts for
12 papers
Spatial Audio Question Answering and Reasoning on Dynamic Source Movements
Arvind Krishna Sridhar, Yinyi Guo, Erik Visser
Spatial audio understanding aims to enable machines to interpret complex auditory scenes, particularly when sound sources move over time. In this work, we study Spatial Audio Quest…
Proactive Conversational Assistant for a Procedural Manual Task based on Audio and IMU
Rehana Mahfuz, Yinyi Guo, Erik Visser +1
Real-time conversational assistants for procedural manual tasks often depend on video input, which can be computationally expensive and compromise user privacy. For the first time,…
Event-Grounded Question Answering over Long Audio via Structured Retrieval
Kartik Hegde, Arvind Krishna Sridhar, Naveen Vakada +2
Answering natural-language questions over multi-hour audio requires reliable event recognition, temporal grounding, and efficient retrieval. We present LA-RAG (Long Audio Retrieval…
Spatial Audio Motion Understanding and Reasoning
Arvind Krishna Sridhar, Yinyi Guo, Erik Visser
Spatial audio reasoning enables machines to interpret auditory scenes by understanding events and their spatial attributes. In this work, we focus on spatial audio understanding wi…
Aligning Audio Captions with Human Preferences
Kartik Hegde, Rehana Mahfuz, Yinyi Guo +1
Current audio captioning relies on supervised learning with paired audio-caption data, which is costly to curate and may not reflect human preferences in real-world scenarios. To a…
Comprehensive Audio Query Handling System with Integrated Expert Models and Contextual Understanding
Vakada Naveen, Arvind Krishna Sridhar, Yinyi Guo +1
This paper presents a comprehensive chatbot system designed to handle a wide range of audio-related queries by integrating multiple specialized audio processing models. The propose…
Resource-Efficient Reference-Free Evaluation of Audio Captions
Rehana Mahfuz, Yinyi Guo, Erik Visser
To establish the trustworthiness of systems that automatically generate text captions for audio, images and video, existing reference-free metrics rely on large pretrained models w…
Enhancing Temporal Understanding in Audio Question Answering for Large Audio Language Models
Arvind Krishna Sridhar, Yinyi Guo, Erik Visser
The Audio Question Answering (AQA) task includes audio event classification, audio captioning, and open-ended reasoning. Recently, AQA has garnered attention due to the advent of L…
Parameter Efficient Audio Captioning With Faithful Guidance Using Audio-text Shared Latent Representation
Arvind Krishna Sridhar, Yinyi Guo, Erik Visser +1
There has been significant research on developing pretrained transformer architectures for multimodal-to-text generation tasks. Albeit performance improvements, such models are fre…
Detecting False Alarms and Misses in Audio Captions
Rehana Mahfuz, Yinyi Guo, Arvind Krishna Sridhar +1
Metrics to evaluate audio captions simply provide a score without much explanation regarding what may be wrong in case the score is low. Manual human intervention is needed to find…
Improving Audio Captioning Using Semantic Similarity Metrics
Rehana Mahfuz, Yinyi Guo, Erik Visser
Audio captioning quality metrics which are typically borrowed from the machine translation and image captioning areas measure the degree of overlap between predicted tokens and gol…
Incremental Learning Algorithm for Sound Event Detection
Eunjeong Koh, Fatemeh Saki, Yinyi Guo +2
This paper presents a new learning strategy for the Sound Event Detection (SED) system to tackle the issues of i) knowledge migration from a pre-trained model to a new target model…