SBIR Phase I: A Cloud-Based Service for Audio Access to News and Blogs

当内容被自动转换为音频格式（如mp3）时，该创新改进了在线书面内容的访问和发现。通常，来自随机书面文本的合成音频通常提供较差的收听体验。技术努力的动机是缺乏向用户提供具有高质量合成音频的优选新闻文章和博客的应用，所述高质量合成音频对于视觉受损的人或诸如汽车驾驶员的多任务视觉忙碌的人来说是语音正确的。这项工作使用的技术，如文本处理的文本理解和内容分析领域知识和机器学习的动机。 机器学习技术用于改进语音合成，并将用户偏好的自动发现纳入可播放的新闻中。由于通过倾听进行内容扫描的过程比视觉扫描相关响应的过程要慢，因此这项技术工作将通过将用户输入与信息检索相结合来改善这种听觉搜索过程，以获得更流畅的用户体验。由此产生的技术基础设施预计将提供一系列具有深远影响的引人注目的商业产品。这项技术工作的更广泛/商业影响来自基于云的基础设施，可以将在线书面文本处理为高质量的音频。 该云软件具有无限存储和计算能力的优势，并使用此来支持内容检索，机器学习，文本预处理，内容发现，自然语言处理以及与商业文本到语音服务器的交互。这项技术的第一个版本将集中在新闻和博客上，这是一个足够大的信息库，在提供相当大的商业利益的同时也提供了挑战。 云基础设施可以支持在智能手机、平板电脑和台式机上运行的一系列客户端应用程序。这些应用程序将能够获得高质量的合成音频，可用于“眼睛繁忙”的情况，包括低视力社区。 这些应用程序将通过智能信息检索提供对用户首选内容的可定制访问。虽然这种客户端应用程序具有商业潜力，但更大的价值来自服务器技术的许可。 这种产品的社会影响是巨大的，因为无论是盲人社区还是普通公众都无法轻松地收听到大量的在线内容，这些内容是根据用户偏好和完全通过语音和手指手势的应用程序控制机制来策划的。

The innovation improves access and discovery of online written content when content is automatically converted to an audio format such as mp3. In general, synthesized audio from random written text often delivers a poor listening experience. The technical effort is motivated by the absence of applications that provide a user preferred news articles and blogs with high quality synthesized audio that is phonetically correct for the visually impaired person or the multitasking visually busy person such as a car driver. This work uses techniques such as textual processing motivated by text understanding and content analysis by domain knowledge and machine learning. Machine learning techniques are used to improve speech synthesis and to incorporate auto-discovery of user preferences into listenable news. Since content scanning by listening is a slower process than visually scanning for relevant responses, this technical work will improve this auditory search process by combining user input with information retrieval for a smoother user experience. The resulting technology infrastructure is expected to provide an array of compelling commercial products with far-reaching implications.The broader/commercial impact of this technical work comes from the cloud-based infrastructure that can process online written text into high-quality audio. This cloud software has advantages of unlimited storage and computing capacity, and uses this to support content retrieval, machine learning, text preprocessing, content discovery, natural language processing, and interaction with commercial Text-to-Speech servers. The first version of this technology will focus on news and blogs, a sufficiently large corpus of information that provides a challenge while also providing considerable commercial interest. The cloud infrastructure can support a range of client-side applications that work on smart-phones, tablets, and desktops. These applications will have access to high quality synthesized audio useable in an "eyes-busy" situation including the low-vision community. The apps will provide customizable access to user-preferred content via intelligent information retrieval. While there is commercial potential in such client applications, the greater value is from licensing the server technology. The societal impact of such a product is tremendous since neither the blind community nor the general public have such easy listening access to the large corpus of online content that is curated with user preferences and with an application control mechanism that is entirely via voice and finger gestures.