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    • 77. 发明申请
    • CONCEPT BASED CROSS MEDIA INDEXING AND RETRIEVAL OF SPEECH DOCUMENTS
    • 基于概念的跨媒体索引和检索语音文档
    • WO2007143109A2
    • 2007-12-13
    • PCT/US2007012965
    • 2007-06-01
    • TELCORDIA TECH INCBEHRENS CLIFFORD AEGAN DENNISBASSU DEVASIS
    • BEHRENS CLIFFORD AEGAN DENNISBASSU DEVASIS
    • G06F17/30
    • G06F17/30746G06F17/30681
    • Indexing, searching, and retrieving the content of speech documents (including but not limited to recorded books, audio broadcasts, recorded conversations) is accomplished by finding and retrieving speech documents that are related to a query term at a conceptual level, even if the speech documents does not contain the spoken (or textual) query terms. Concept-based cross-media information retrieval is used. A term-phoneme/document matrix is constructed from a training set of documents. Documents are then added to the matrix constructed from the training data. Singular Value Decomposition is used to compute a vector space from the term-phoneme/document matrix. The result is a lower-dimensional numerical space where term-phoneme and document vectors are related conceptually as nearest neighbors. A query engine computes a cosine value between the query vector and all other vectors in the space and returns a list of those term-phonemes and/or documents with the highest cosine value.
    • 索引,搜索和检索语音文档的内容(包括但不限于记录的书籍,音频广播,记录的对话)通过在概念层面上查找和检索与查询词相关的语音文档来实现,即使语音 文件不包含口头(或文字)查询条款。 使用基于概念的跨媒体信息检索。 术语音素/文件矩阵是由一组文件组成的。 然后将文档添加到从训练数据构建的矩阵中。 奇异值分解用于从术语 - 音素/文档矩阵中计算向量空间。 结果是一个低维数值空间,其中术语音素和文档向量在概念上作为最近的邻居相关。 查询引擎计算查询向量和空间中所有其他向量之间的余弦值,并返回具有最高余弦值的那些术语音素和/或文档的列表。