Topic indexing of spoken documents based on optimized N-best approach

For topic indexing of spoken documents, the word error rate is hopefully decreased instead of the whole sentence error rate, so the center hypothesis among the N-best results is selected as the final output in speech recognition system. Then all spoken documents can be represented as vectors with hi...

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Bibliographische Detailangaben

Hauptverfasser:	Lei Zhang, Jingxin Chang, Xuezhi Xiang, Xiaosen Feng
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Decoding Educational institutions Error analysis Indexing Information retrieval Lattices Matrix decomposition NMF optimaized N-best Signal processing algorithms Singular value decomposition Speech recognition SVD Topic indexing
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