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Zhikang Niu

7 accepted papers

2026

STAR-Bench: Probing Deep Spatio-Temporal Reasoning as Audio 4D Intelligence

ICLR 2026poster

Despite rapid progress in Multi-modal Large Language Models and Large Audio-Language Models, existing audio benchmarks largely test semantics that can be recovered from text captions, masking deficits in fine-grained perceptual reasoning. We formalize audio 4D intelligence that is defined as reasoni…

Cited by 8SourcecodeScholar
2026

WaveEx: Accelerating Flow Matching-based Speech Generation via Wavelet-guided Extrapolation

AAAI 2026technical

Flow matching-based generative models offer a principled approach to modeling continuous-time dynamics in speech generation. However, inference is often computationally expensive due to repeated neural network evaluations required by ODE solvers. We propose WaveEx, a training-free and plug-in accele

Cited by 0SourcePDFScholar
2025

F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching

ACL 2025long

This paper introduces F5-TTS, a fully non-autoregressive text-to-speech system based on flow matching with Diffusion Transformer (DiT). Without requiring complex designs such as duration model, text encoder, and phoneme alignment, the text input is simply padded with filler tokens to the same length…

2025

MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix

NeurIPS 2025poster

We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,000 meticulously curated audio-question-answer triplets, collected from real-world internet videos and refined through ite…

Cited by 0SourcecodeScholar
2025

SLAM-Omni: Timbre-Controllable Voice Interaction System with Single-Stage Training

ACL 2025finding

Recent advancements highlight the potential of end-to-end real-time spoken dialogue systems, showcasing their low latency and high quality. In this paper, we introduce SLAM-Omni, a timbre-controllable, end-to-end voice interaction system with single-stage training. SLAM-Omni achieves zero-shot timbr…

2025

URO-Bench: Towards Comprehensive Evaluation for End-to-End Spoken Dialogue Models

EMNLP 2025

Recent advances in large language models (LLMs) have driven significant progress in end-to-end spoken dialogue models (SDMs). In contrast to text-based LLMs, the evaluation framework for SDMs should encompass both cognitive dimensions (e.g., logical reasoning, knowledge) and speech-related aspects (

2025

VALL-T: Decoder-Only Generative Transducer for Robust and Decoding-Controllable Text-to-Speech

ICASSP 2025accepted

Recent TTS models with decoder-only Transformer architecture, such as SPEAR-TTS and VALL-E, achieve impressive naturalness and demonstrate the ability for zero-shot adaptation given a speech prompt. However, such decoder-only TTS models lack monotonic alignment constraints, sometimes leading to hall…

Cited by 0SourceScholar