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Jfkunsified
案例简介：执行 达拉斯贸易市场的演讲是世界第一的，一个人工智能音频演讲完全由数百个不同质量和音频的旧演讲的数据制作而成。这项突破性技术涉及智能拼接语音的小语音片段-通常约250,000个单独的片段，持续时间低至3毫秒。通过数月的艰苦的声音工程来选择和平滑声音的组合。处决使我们的读者终于听到了肯尼迪自己的声音发表的贸易市场演讲。位置: 在线规模: 超过10亿媒体印象品牌相关性: 这个想法是为了帮助发起《泰晤士报》 “找到你的声音” 活动。接触点: 在线、报纸、广播、播客。材料，风格元素，设计选择: 与音频思想方法和过程无关这项突破性技术涉及智能拼接语音的小语音片段-通常约250,000个单独的片段，持续时间缩短至3毫秒。经过数月的艰苦的声音工程，可以选择声音的组合并将其平滑化。执行过程使我们的读者最终能够听到肯尼迪自己的声音发表的Trade Mart演讲。时间轴这个想法在经过数月的艰苦的声音设计后于3月推出。 运动描述 1963年，没有人听到肯尼迪总统非常重要的贸易市场演讲。2018年，以声音设计和音频技术形式的数字工艺使他的无声演讲引起了超过10亿人的注意。
Jfkunsified
案例简介：Execution The Dallas Trade Mart Speech is a world first, an Ai audio speech made completely out of data from hundreds of old speeches of varying quality and audio. This breakthrough technique involves smart splicing small phonetic fragments of speech - typically around 250,000 individual segments, down to 3milliseconds in duration. Combinations of sounds are selected and smoothed together by months of painstaking sound engineering. The execution allowed our readers to finally hear the Trade Mart Speech delivered in JFK’s own voice. Placement : Online Scale : Over 1 billion media impressions Brand relevance : This idea was to help launch the Times ‘Find your voice’ campaign. Touch point : Online, Newspaper, radio, podcast. Materials, style elements, design choices : Not relevant to audio idea Methods and process This breakthrough technique involves smart splicing small phonetic fragments of speech - typically around 250,000 individual segments, down to 3milliseconds in duration. Combinations of sounds are selected and smoothed together by months of painstaking sound engineering The execution allowed our readers to finally hear the Trade Mart Speech delivered in JFK’s own voice. Timeline The idea launched in March after months of painstaking sound design. CampaignDescription In 1963 nobody got to hear President Kennedy’s hugely important Trade Mart Speech. In 2018, digital craft in the form of sound design & audio technology brought his Unsilenced speech to the attention of over 1 billion people.
JFKunsilenced
案例简介：执行 达拉斯贸易市场的演讲是世界第一的，一个人工智能音频演讲完全由数百个不同质量和音频的旧演讲的数据制作而成。这项突破性技术涉及智能拼接语音的小语音片段-通常约250,000个单独的片段，持续时间低至3毫秒。通过数月的艰苦的声音工程来选择和平滑声音的组合。处决使我们的读者终于听到了肯尼迪自己的声音发表的贸易市场演讲。位置: 在线规模: 超过10亿媒体印象品牌相关性: 这个想法是为了帮助发起《泰晤士报》 “找到你的声音” 活动。接触点: 在线、报纸、广播、播客。材料，风格元素，设计选择: 与音频思想方法和过程无关这项突破性技术涉及智能拼接语音的小语音片段-通常约250,000个单独的片段，持续时间缩短至3毫秒。经过数月的艰苦的声音工程，可以选择声音的组合并将其平滑化。执行过程使我们的读者最终能够听到肯尼迪自己的声音发表的Trade Mart演讲。时间轴这个想法在经过数月的艰苦的声音设计后于3月推出。 运动描述 1963年，没有人听到肯尼迪总统非常重要的贸易市场演讲。2018年，以声音设计和音频技术形式的数字工艺使他的无声演讲引起了超过10亿人的注意。
JFKunsilenced
案例简介：Execution The Dallas Trade Mart Speech is a world first, an Ai audio speech made completely out of data from hundreds of old speeches of varying quality and audio. This breakthrough technique involves smart splicing small phonetic fragments of speech - typically around 250,000 individual segments, down to 3milliseconds in duration. Combinations of sounds are selected and smoothed together by months of painstaking sound engineering. The execution allowed our readers to finally hear the Trade Mart Speech delivered in JFK’s own voice. Placement : Online Scale : Over 1 billion media impressions Brand relevance : This idea was to help launch the Times ‘Find your voice’ campaign. Touch point : Online, Newspaper, radio, podcast. Materials, style elements, design choices : Not relevant to audio idea Methods and process This breakthrough technique involves smart splicing small phonetic fragments of speech - typically around 250,000 individual segments, down to 3milliseconds in duration. Combinations of sounds are selected and smoothed together by months of painstaking sound engineering The execution allowed our readers to finally hear the Trade Mart Speech delivered in JFK’s own voice. Timeline The idea launched in March after months of painstaking sound design. CampaignDescription In 1963 nobody got to hear President Kennedy’s hugely important Trade Mart Speech. In 2018, digital craft in the form of sound design & audio technology brought his Unsilenced speech to the attention of over 1 billion people.
Jfkunsified
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JFKunsilenced
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