---
格式版本: 2
标题: "Alibaba Releases AI Music Generation Model HappyShrimp 1.0 in Beta Test"
原文链接: "https://www.alibabacloud.com/blog/alibaba-releases-ai-music-generation-model-happyshrimp-1-0-in-beta-test_603466"
发布日期: "2026-08-18"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "llm:scrape:extracted_text"
发布时间证据: "第 21 行：August 18, 2026"
发布时间校准原因: "该日期位于文章正文区域，与发现时间吻合，且其他候选均带有社区前缀，疑似为其他相关文章日期。"
发布时间校准置信度: "1"
发布时间候选数量: 7
发布时间严格候选数量: 0
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-21T09:59:29+08:00"
发布时间仲裁状态: "confirmed"
发布时间仲裁尝试次数: 2
发布时间仲裁耗时毫秒: 14851
发现时间: "2026-08-21T09:56:50+08:00"
入库时间: "2026-08-21T01:59:44.266Z"
来源平台: "固定入口"
搜索渠道: "fixed_url"
搜索词: "https://www.alibabacloud.com/blog"
匹配关键词:
  - "AI"
  - "Immersion"
  - "performance"
相关厂家:
  - "阿里"
相关专家:
  []
内容类型: "网页"
抓取工具: "Free Fetch + Defuddle"
清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 5
AI分档: "非优质"
AI质检状态: "不通过"
AI打分理由: "内容为阿里AI音乐生成模型HappyShrimp，与超节点、AI Rack、机柜级AI基础设施、供电散热互连等主题完全无关，仅命中泛AI关键词，不构成有效技术信号。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-21T09:59:48+08:00"
AI主题相关性: 0
AI来源权威性: 5
AI新颖性: 0
AI技术细节: 0
AI商业部署信号: 0
AI完整性: 0
AI摘要: "阿里云旗下阿里Token Hub发布AI音乐生成模型HappyShrimp 1.0测试版，用户输入情绪、故事或风格等单一提示即可生成带歌词和演唱的完整歌曲，无需乐理知识。该模型已与太合音乐集团合作探索艺人共创等内容开发。"
AI摘要模型: "ali-deepseek-v4-flash"
AI摘要时间: "2026-09-07T02:13:07.749Z"
采集批次: "2026年8月21日9点50分40秒"
采集批次ID: "20260821-095040-035"
去重键: "https://www.alibabacloud.com/blog/alibaba-releases-ai-music-generation-model-happyshrimp-1-0-in-beta-test_603466"
---

Alibaba has launched the beta version of HappyShrimp 1.0, an AI music generation model developed by its Alibaba Token Hub (ATH) business group, for users to turn vague ideas into a fully produced song.

HappyShrimp 1.0 allows users to generate complete tracks from a single prompt, whether based on an emotion, a story concept, or a target genre. The model can produce melody, arrangement, lyrics, and vocals without requiring technical music knowledge such as BPM, key signature, or instrumentation.

In its beta release, the model supports text-to-music (T2M) generation for both full vocal songs and instrumental compositions. Users can either create an entire track, including lyrics, from scratch, or provide their own lyrics and have the model generate the composition, arrangement, and vocal performance.

HappyShrimp 1.0 is built with broad musical knowledge to understand the creative aesthetics underlying various genres, regions, eras, and cultural contexts. It can interpret prompts such as “millennial Mandarin pop,” “the dawn-like sensibility of urban folk,” or “opera-style vocals in the chorus” and translate them into structured musical outputs. It demonstrates outstanding performance across genres including Chinese style (Zhongguo feng), pop, R&B/soul, hip hop, rock, funk, electronic, classical, and jazz.

<video width="100%" height="100%" src="https://video-intl.alicdn.com/2026/Blog/Bow-Down.mp3" controls=""></video>  
***Creator's Note***: I simply asked for a K-pop girl-group track in the prompt, but HappyShrimp interpreted it well and independently crafted the melody, arrangement, vocals, and rap flows in the style of K-pop aesthetic. The melodies unfold smoothly, while the rap sections feature varied flows and deft rhythmic shifts in the bridge. Paired with an explosive drop, the arrangement instantly establishes a powerful rhythmic foundation.

Utilizing its world knowledge and music-domain reasoning, HappyShrimp 1.0 builds a structured representation of both the “grammar” of music — such as song structure, rhythmic development, and harmonic progression — and its “semantics,” including emotional tone, energy profile, and lyrical intent. This enables the model to fully comprehend user input and generate music that more accurately aligns with creative intent.

This gives the model precise controllability, enabling user-defined narrative flow, instrumentation, vocal style, and emotional dynamics to be accurately reflected in the generated tracks.

<video width="100%" height="100%" src="https://video-intl.alicdn.com/2026/Blog/HappyShimp-demo.wav" controls=""></video>  
***Creator's note***: This Future Garage track is exceptionally refined in both timbral design and spatial treatment. The overall mix is clean and crystalline, with well-controlled dynamics and smooth, clearly defined transitions between sections. It not only showcases the futuristic, high-tech edge of electronic music, but also perfectly captures the cold, ethereal atmosphere of “glacial melting” described in the prompt. The piece has a strong documentary-like quality, making it especially well suited for videos featuring glaciers, snowfields, wildlife, nature exploration, or environmental themes, enhancing both immersion and epic scale.

HappyShrimp will collaborate with TAIHE MUSIC GROUP, a leading music service provider in China. Combining HappyShrimp's advanced AI technology with TAIHE's expertise in music ecosystem, the two will explore opportunities in initiatives such as artist co-creation, and high-quality content development.

**HappyShrimp 1.0 can be accessed via official website** [https://www.happyshrimp.ai/](https://www.happyshrimp.ai/)

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*This article was originally published on [Alizila](https://www.alizila.com/alibaba-releases-ai-music-generation-model-happyshrimp-1-0-in-beta-test/) written by Claire Mo*