While human evaluation is the most reliable metric for evaluating speech generation systems, it is generally costly and time-consuming. Previous studies on automatic speech quality assessment address the problem by predicting human evaluation scores with machine learning models. However, they rely on supervised learning and thus suffer from high annotation costs and domain-shift problems. We propose SpeechLMScore, an unsupervised metric to evaluate generated speech using a speech-language model. SpeechLMScore computes the average log-probability of a speech signal by mapping it into discrete tokens and measures the average probability of generating the sequence of tokens. Therefore, it does not require human annotation and is a highly scalable framework. Evaluation results demonstrate that the proposed metric shows a promising correlation with human evaluation scores on different speech generation tasks including voice conversion, text-to-speech, and speech enhancement.
STEB: A Speech-to-Speech Translation Expressiveness Benchmark for Evaluating Beyond Translation Fidelity
Hong Kong University of Science and Technology（香港科技大学）；Tencent Youtu Lab（腾讯优图实验室）；Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）
VoxPrivacy: A Benchmark for Evaluating Interactional Privacy of Speech Language Models
The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Loop Area Institute（深圳河套学院）；Amphion Technology Co., Ltd.（安丰科技有限公司）；Shenzhen Research Institute of Big Data（深圳大数据研究院）
Hearing is Believing? Evaluating and Analyzing Audio Language Model Sycophancy with SYAUDIO
University of Electronic Science and Technology of China（电子科技大学）；Mohamed bin Zayed University of Artificial Intelligence（Mohamed bin Zayed人工智能大学）；King Abdullah University of Science and Technology（卡布斯大学）；Georgia Institute of Technology（佐治亚理工学院）
Designing and Evaluating Speech Emotion Recognition Systems: A reality check case study with IEMOCAP
Behavioral Signal Technologies（行为信号技术公司）；Institute for Language and Speech Processing, Athena Research Center（雅典娜研究中心语言与语音处理研究所）；University of Southern California（南加州大学）
The VoiceMOS Challenge 2026: Evaluating Speech Enhancement, Emotional TTS and Accented TTS Systems
Nagoya University（名古屋大学）；Shanghai Jiao Tong University（上海交通大学）；Technische Universität Braunschweig（布伦瑞克工业大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；University of Edinburgh（爱丁堡大学）；National Institute of Information and Communications Technology（日本国立信息通信技术研究所）
Evaluating the Intelligibility Benefits of Neural Speech Enrichment for Listeners with Normal Hearing and Hearing Impairment using the Greek Harvard Corpus
University of Crete（克里特大学）；Chania General Hospital（干尼亚综合医院）
Enhancing Indonesian Automatic Speech Recognition: Evaluating Multilingual Models with Diverse Speech Variabilities
Institut Teknologi Bandung（万隆理工学院）；University of Indonesia（印度尼西亚大学）；Japan Advanced Institute of Science and Technology（日本先进科学技术学院）；Nara Institute of Science and Technology（奈良科学技术大学）
S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models
Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology（深圳先进技术研究院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Nanjing University（南京大学）；Shenzhen Loop Area Institute（深圳河套学院）；CentraleSupélec, Université Paris-Saclay（巴黎萨克雷大学CentraleSupélec分校）；National University of Singapore（新加坡国立大学）
Evaluating Self-supervised Speech Models on a Taiwanese Hokkien Corpus
Carnegie Mellon University（卡内基梅隆大学）；Scripps College（斯克里普斯学院）；University of Maryland（马里兰大学）；Swarthmore College（斯沃斯莫尔学院）；National Taiwan Normal University（国立台湾师范大学）；China Medical University, Taiwan（中国医药大学（台湾））；National Taiwan University（国立台湾大学）
Evaluating Parkinson's Disease Detection in Anonymized Speech: A Performance and Acoustic Analysis
German Research Center for Artificial Intelligence（德国人工智能研究中心）；INESC-ID；Technical University of Berlin（柏林技术大学）；Instituto Superior Técnico, University of Lisbon（里斯本大学理工学院）
Towards Evaluating the Robustness of Automatic Speech Recognition Systems via Audio Style Transfer
Beijing University of Posts and Telecommunications（北京邮电大学）；Tsinghua University（清华大学）；CSIRO’s Data61（澳大利亚联邦科学与工业研究组织Data61）；Nanyang Technological University（南洋理工大学）
Evaluating Parameter-Efficient Transfer Learning Approaches on SURE Benchmark for Speech Understanding
Beijing University of Posts and Telecommunications（北京邮电大学）；University of Michigan（密歇根大学）；Singapore University of Technology and Design（新加坡科技设计大学）；Amazon Science（亚马逊科学）
Evaluating Speech-in-Speech Perception via a Humanoid Robot
University Medical Center Groningen（格罗宁根大学医学中心）；University of Groningen（格罗宁根大学）；Pento Audiology Centre（Pento听力中心）；Lyon Neuroscience Research Center（里昂神经科学研究中心）；Université Claude Bernard Lyon 1（里昂第一大学）；Université de Lyon（里昂大学）
