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Showing Spoken language models Show all papers

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NeurIPS 2026TsinghuaTsinghua University, TsinghuaSpoken language models

Speak Early: Speculative Speech Generation for Low-Latency SpeechLLMs

Tianyuan Jiang, Yongheng Deng, Ju Ren

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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57%Worth a look
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NeurIPS 2026Xi'an Jiaotong-LiverpoolThe Chinese University of Hong KSpoken language models

Enhancing Speech Large Language Models through Reinforced Behavior Alignment

Yansong Liu, Yuan Liu

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026ConcordiaUbisoftU StellenboschSpoken language models

Factorized Self-Supervised Speech Tokenization

Benjamin Van Niekerk, Jean-Philippe Letendre, Nicol Visser, Hugo Seuté and 2 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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67%Highly rated
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NeurIPS 2026The Chinese University of Hong KMicrosoftChinese University of Hong Kong,Spoken language models

Is Text All You Need? Text as a Universal Information Bottleneck for Speech LLMs

Ming-Hao Hsu, Yuxuan Hu, Shujie LIU, Jinyu Li and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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lenient 0/5
medium 1/10
strict 1/5
86%Must read
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NeurIPS 2026The Chinese University of Hong KShanghai JiaotongSenseTime ReseachSpoken language models

MultiTalk: Scaling Full-Duplex Speech Models to Long, Multi-Party, Bilingual Conversation

MultiTalk introduces 57.6k hours of synthetic multi-party bilingual dialogue data and MultiTalkBench for long-form full-duplex evaluation, training a model that sustains coherent extended multi-party English-Chinese conversation and outperforms open-source baselines.

Ke Wang, Houxing Ren, Zimu Lu, Yunqiao Yang and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
80%Must read
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NeurIPS 2026China TelecomChina Telecom Artificial IntelliTianjinTsinghua University, TsinghuaSpoken language models

TELEVAL: A Benchmark Designed for Spoken Language Models in Chinese Interactive Scenarios

TELEVAL benchmarks Chinese spoken language models on interactional audio-conditioned dialogue, finding competitive semantic accuracy but degraded interactional performance under acoustic variability and a recurring caption trap failure.

Zehan Li, Hongjie Chen, Qing Wang, Yuxin Zhang and 8 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5