most citedGOAT-TTS: Expressive and Realistic Speech Generation via A Dual-Branch LLM

1 citations · 2 across the 9 of their papers we have counts for

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cs.CL2026

A Unified Spoken Language Model with Injected Emotional-Attribution Thinking for Human-like Interaction

Qing Wang, Zehan Li, Yaodong Song +6

This paper presents a unified spoken language model for emotional intelligence, enhanced by a novel data construction strategy termed Injected Emotional-Attribution Thinking (IEAT)…

cs.CL2025

GOAT-SLM: A Spoken Language Model with Paralinguistic and Speaker Characteristic Awareness

Hongjie Chen, Zehan Li, Yaodong Song +13

Recent advances in end-to-end spoken language models (SLMs) have significantly improved the ability of AI systems to engage in natural spoken interactions. However, most existing m…

cs.CL2025

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

Zehan Li, Hongjie Chen, Qing Wang +9

Spoken Language Models (SLMs) are expected to support natural spoken interaction beyond task completion. However, existing SLM benchmarks primarily evaluate semantic correctness in…

cs.CL2025

Leveraging LLM and Self-Supervised Training Models for Speech Recognition in Chinese Dialects: A Comparative Analysis

Tianyi Xu, Hongjie Chen, Wang Qing +6

Large-scale training corpora have significantly improved the performance of ASR models. Unfortunately, due to the relative scarcity of data, Chinese accents and dialects remain a c…

cs.CL2025★ 1 cited

GOAT-TTS: Expressive and Realistic Speech Generation via A Dual-Branch LLM

Yaodong Song, Hongjie Chen, Jie Lian +8

While large language models (LLMs) have revolutionized text-to-speech (TTS) synthesis through discrete tokenization paradigms, current architectures exhibit fundamental tensions be…