Core Viewpoint - The article discusses the advancements and performance of various AI voice synthesis models, particularly focusing on their emotional expression capabilities in different scenarios such as live streaming, companionship, and audiobooks. It highlights the progress made in the AI voice sector while also pointing out the limitations that still exist in emotional conveyance and scene adaptation [3][32]. Group 1: AI Voice Model Performance - In February, a test was conducted on four AI voice synthesis models using segments from the popular drama "Zhen Huan Zhuan," revealing that the models still lack sufficient emotional expressiveness [3]. - The latest version of MiniMax's Speech-02-HD model topped the rankings in both the Artificial Analysis Speech Arena and Hugging Face TTS Arena, outperforming competitors in objective metrics like error rate and voice similarity [4]. - Several companies, including Cartesia and Hume AI, have secured significant funding for their AI voice products, indicating a competitive landscape in the AI voice synthesis market [5]. Group 2: Testing Methodology - The testing expanded to include three representative scenarios: live streaming, companionship, and audiobooks, with five models selected for evaluation based on rankings and reader recommendations [6][9]. - Objective testing was conducted using Alibaba's SenseVoice model to assess emotional recognition, followed by subjective evaluations from a panel of editors [10][9]. Group 3: Scenario-Specific Performance - In the audiobook scenario, DubbingX performed notably well, particularly in conveying anger and sadness, while other models struggled to meet the emotional requirements [11][16]. - For the live streaming scenario, all tested models passed objective tests but failed to meet subjective evaluation standards due to a lack of rhythm and authenticity compared to human hosts [25]. - In the companionship scenario, models showed moderate performance, successfully conveying warmth and positivity, although some AI characteristics remained evident [28]. Group 4: Industry Insights - The article notes that while AI voice models have made some progress in emotional expression, they still struggle with complex emotional situations and require further engineering optimization to adapt to real-world applications [32][36]. - DubbingX's success in the Chinese audiobook market is attributed to its detailed emotional tagging, which enhances its performance in specific contexts compared to models lacking such features [33][36]. - The AI voice generation technology is increasingly being applied across various sectors, indicating a growing trend towards more intelligent and versatile applications in the near future [38].