VoxENES 2026: Benchmarking Speech Spoofing Detectors Against LLM TTS & VC

The evolution of large language model-driven text-to-speech (TTS) and voice conversion (VC) systems has reached a level of realism that challenges traditional fake voice detectors. Legacy spoofing benchmarks, such as those used in past competitions, have become obsolete when faced with modern generators, creating a temporal gap that can overestimate detection robustness under real-world post-processing conditions. In this context, VoxENES 2026 emerges as a bilingual (English and Spanish) benchmark consisting of 53,628 audio samples generated using 10 contemporary speech synthesis methods and evaluated under 10 standardized post-processing conditions. This resource enables precise measurement of the degradation suffered by pretrained detectors without fine-tuning, revealing a worrying reality: the best model achieves a 28.98% equal error rate (EER), while most operate near or below random chance. These results show that current detectors rely on fragile and poorly generalizable artifacts. For companies aiming to protect their communication systems, this gap represents a critical cybersecurity risk. At Q2BSTUDIO, as a software development and technology company, we understand that synthetic audio detection cannot be solved with static solutions. Our expertise in custom software development allows us to create AI models trained specifically with up-to-date data, including the latest generators. Additionally, we combine this capability with cloud infrastructures such as AWS and Azure to process large volumes of audio in real time, and with Business Intelligence tools like Power BI to monitor detection system effectiveness. AI agents also play a key role: they can analyze voice patterns and dynamically adapt to new impersonation techniques. For example, a custom software solution can integrate a voice verification module that uses continuous learning to stay current with emerging threats. Likewise, Q2BSTUDIO's AI services enable the implementation of deep neural network-based detectors that not only identify fragile artifacts but learn to recognize the underlying statistical characteristics of synthetic speech. In an environment where attackers use state-of-the-art TTS and VC to bypass biometric authentication, having a robust cybersecurity strategy is essential. Our pentesting and security consulting services help organizations assess vulnerabilities in their voice systems. Furthermore, process automation through AI agents enables scalable monitoring without human intervention. VoxENES 2026 reminds us that spoofing detection research must advance at the same pace as synthetic speech generation. Companies investing in custom software development, cloud computing, and data analytics will be better prepared to face these challenges. At Q2BSTUDIO we offer a complete ecosystem of technological solutions, from AI model implementation to integration with BI platforms like Power BI, ensuring that fake voice detection is not a blind spot in corporate security strategies.