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20242026
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eess.AS2026

AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering

Chun-Yi Kuan, Kai-Wei Chang, Hung-yi Lee

Although text-to-audio generation has made remarkable progress in realism and diversity, the development of evaluation metrics has not kept pace. Widely-adopted approaches, typical…

eess.AS2025

Full-Duplex-Bench-v2: A Multi-Turn Evaluation Framework for Duplex Dialogue Systems with an Automated Examiner

Guan-Ting Lin, Shih-Yun Shan Kuan, Jiatong Shi +4

While full-duplex speech agents enable natural, low-latency interaction by speaking and listening simultaneously, their consistency and task performance in multi-turn settings rema…

eess.AS2025

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

Kai-Wei Chang, En-Pei Hu, Chun-Yi Kuan +7

Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of temporal dynamics, including the abil…

eess.AS2025

DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment

Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25

We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…

eess.AS2025

SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning

Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4

We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…

eess.AS2024

Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models

Haibin Wu, Xuanjun Chen, Yi-Cheng Lin +13

Neural audio codec models are becoming increasingly important as they serve as tokenizers for audio, enabling efficient transmission or facilitating speech language modeling. The i…