Method and system for retrieving documents with spoken queries
AssigneeMitsubishi Electric Research Laboratories, Inc.
InventorsPeter P. Wolf, Bhiksha Ramakrishnan
Life of this patent
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Abstract
A system and method indexes and retrieves documents stored in a database. A document feature vector is extracted for each document to be indexed. The feature vector is projected to a low dimension document feature vector, and the documents are indexed according to the low dimension document feature vectors. A spoken query is represented as a lattice indicating possible sequential combinations of words in the spoken query. The lattice is converted to a query certainty vector, which is also projected to a low dimension query certainty vector. The low dimension query vector is compared to each of the low dimension document feature vectors to retrieve a matching result set of documents.
Claims19
A computer-implemented method for indexing and retrieving documents stored in a database, comprising:
- extracting a document feature vector for each of a plurality of documents;
- projecting each document feature vector to a low dimension document feature vector;
- indexing each of the plurality of documents according the associated low dimension document feature vector in the database;
- representing a spoken query as a lattice, the lattice representing likely possible sequential combinations of words in the spoken query;
- converting the lattice to a query certainty vector;
- projecting the query certainty vector to an associated low dimension query certainty vector;
- comparing the low dimension query vector to each of the low dimension document feature vectors;
- and
- retrieving a result set of documents from the database that have low dimension document feature vectors that match the low dimension query certainty vector.
A computer-implemented system for indexing and retrieving documents in a database, comprising:
- means for extracting a document feature vector for each of a plurality of documents;
- means for projecting each document feature vector to a low dimension document feature vector;
- a database indexing each of the plurality of documents according the associated low dimension document feature vector;
- means for representing a spoken query as a lattice, the lattice representing likely possible sequential combinations of words in the spoken query;
- means for converting the lattice to a query certainty vector;
- means for projecting each query certainty vector to an associated low dimension query certainty vector;
- means for comparing the low dimension query vector to each of the low dimension document feature vectors;
- and
- a search engine configured to retrieve a result set of documents from the database that have low dimension document feature vectors that match the low dimension query certainty vector.
Dependencies are inferred from the claim text.