Papers Audio Question Answering
“Audio Question Answering” 태그가 달린 논문 18편 · 필터 해제
$\mathcal{A}LLM4ADD$: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection
Audio deepfake detection (ADD) has grown increasingly important due to the rise of high-fidelity audio generative models and their potential for misuse. Given that audio large language models (ALLMs) have made significan…
Audio Deepfake DetectionAudio Question AnsweringDeepFake DetectionFace Swapping+1Omni-R1: Do You Really Need Audio to Fine-Tune Your Audio LLM?
We propose Omni-R1 which fine-tunes a recent multi-modal LLM, Qwen2.5-Omni, on an audio question answering dataset with the reinforcement learning method GRPO. This leads to new State-of-the-Art performance on the recent…
Audio Question AnsweringQuestion AnsweringMulti-Domain Audio Question Answering Toward Acoustic Content Reasoning in The DCASE 2025 Challenge
We present Task 5 of the DCASE 2025 Challenge: an Audio Question Answering (AQA) benchmark spanning multiple domains of sound understanding. This task defines three QA subsets (Bioacoustics, Temporal Soundscapes, and Com…
Audio Question AnsweringQuestion AnsweringKimi-Audio Technical Report
We present Kimi-Audio, an open-source audio foundation model that excels in audio understanding, generation, and conversation. We detail the practices in building Kimi-Audio, including model architecture, data curation, …
Audio Question AnsweringQuestion Answeringspeech-recognitionSpeech RecognitionSolla: Towards a Speech-Oriented LLM That Hears Acoustic Context
Large Language Models (LLMs) have recently shown remarkable ability to process not only text but also multimodal inputs such as speech and audio. However, most existing models primarily focus on analyzing input signals u…
Audio captioningAudio Question AnsweringAudio TaggingQuestion AnsweringReinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question Answering
Recently, reinforcement learning (RL) has been shown to greatly enhance the reasoning capabilities of large language models (LLMs), and RL-based approaches have been progressively applied to visual multimodal tasks. Howe…
Audio Question AnsweringQuestion AnsweringReinforcement Learning (RL)Audiopedia: Audio QA with Knowledge
In this paper, we introduce Audiopedia, a novel task called Audio Question Answering with Knowledge, which requires both audio comprehension and external knowledge reasoning. Unlike traditional Audio Question Answering (…
Audio Question AnsweringEntity LinkingQuestion AnsweringEnhancing Temporal Understanding in Audio Question Answering for Large Audio Language Models
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 Large Audio Language Models (LALMs). Curr…
Audio captioningAudio Question AnsweringCPUData Augmentation+2GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities
Perceiving and understanding non-speech sounds and non-verbal speech is essential to making decisions that help us interact with our surroundings. In this paper, we propose GAMA, a novel General-purpose Large Audio-Langu…
Audio Question AnsweringInstruction FollowingLanguage ModelingLanguage Modelling+1Audio Dialogues: Dialogues dataset for audio and music understanding
Existing datasets for audio understanding primarily focus on single-turn interactions (i.e. audio captioning, audio question answering) for describing audio in natural language, thus limiting understanding audio via inte…
Audio captioningAudio Question AnsweringLanguage ModelingLanguage Modelling+2AQUALLM: Audio Question Answering Data Generation Using Large Language Models
Audio Question Answering (AQA) constitutes a pivotal task in which machines analyze both audio signals and natural language questions to produce precise natural language answers. The significance of possessing high-quali…
Audio Question AnsweringQuestion AnsweringAttention-Based Methods For Audio Question Answering
Audio question answering (AQA) is the task of producing natural language answers when a system is provided with audio and natural language questions. In this paper, we propose neural network architectures based on self-a…
Audio Question AnsweringBinary ClassificationQuestion AnsweringMulti-Scale Attention for Audio Question Answering
Audio question answering (AQA), acting as a widely used proxy task to explore scene understanding, has got more attention. The AQA is challenging for it requires comprehensive temporal reasoning from different scales' ev…
Audio Question AnsweringQuestion AnsweringScene UnderstandingVisual Question AnsweringPengi: An Audio Language Model for Audio Tasks
In the domain of audio processing, Transfer Learning has facilitated the rise of Self-Supervised Learning and Zero-Shot Learning techniques. These approaches have led to the development of versatile models capable of tac…
Audio captioningAudio Question AnsweringLanguage ModelingLanguage Modelling+5ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
In this work, we explore a scalable way for building a general representation model toward unlimited modalities. We release ONE-PEACE, a highly extensible model with 4B parameters that can seamlessly align and integrate …
1 Image, 2*2 StitchiAction ClassificationAudioCapsAudio Classification+18Clotho-AQA: A Crowdsourced Dataset for Audio Question Answering
Audio question answering (AQA) is a multimodal translation task where a system analyzes an audio signal and a natural language question, to generate a desirable natural language answer. In this paper, we introduce Clotho…
Audio Question AnsweringQuestion AnsweringTemporal Reasoning via Audio Question Answering
Multimodal question answering tasks can be used as proxy tasks to study systems that can perceive and reason about the world. Answering questions about different types of input modalities stresses different aspects of re…
Audio Question AnsweringDiagnosticQuestion AnsweringReading Comprehension+3XLNet: Generalized Autoregressive Pretraining for Language Understanding
With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling. However, relyi…
Audio Question AnsweringChinese Reading ComprehensionDocument RankingHumor Detection+9