**[Google DeepMind Releases Lyria 3.5 Music Generation Model, Capable of Producing Full Songs up to 3 Minutes Long]** BlockBeats reports that on July 30, Google DeepMind unveiled its next-generation music generation model, Lyria 3.5, which focuses on improving music structure, lyric quality, instruction adherence, vocal performance, and song duration control. The model can directly generate complete songs up to 3 minutes long, rather than just short audio clips of a few seconds. According to the introduction, Lyria 3.5 still employs a latent diffusion architecture, generating through diffusion in the temporal audio latent space. Its training data consists of audio annotated with text at varying levels of granularity. Post-training was conducted using SFT and reinforcement learning combined with human and Critic feedback. All generated content is embedded with SynthID watermarks. However, Google has not disclosed the scale, source, or quantitative benchmarks of the training data, only stating that compared to Lyria 2, significant improvements have been made in audio clarity and adherence to lyric instructions. Additionally, Lyria 3.5 is initially integrated into Flow Music, which supports conversational music creation, stem separation, remixing, music publishing, playlist generation, and can collaborate with Veo to produce music videos. It also supports the development of audio plugins, music games, and custom DAWs, further integrating Lyria, Veo, and Gemini to build a comprehensive ecosystem covering music creation, editing, publishing, and distribution. [Original Link]