Abstract

The paper proposes modifications to improve the recognition performance obtainable by the ETSI standard distributed speech recognition encoder, Aurora (ES 201 108, 2000). The proposed modifications are standard compliant, i.e., they require no algorithmic modifications to the Aurora operation. Performance improvements are achieved by distributing the available bit budget among Aurora's seven (different) 2-dimension vector quantizers (VQs) more efficiently. Improved bit-allocation to the different sub-vectors is achieved by incorporating the importance for recognition of each of the sub-vectors into the bit-allocation algorithm. The available bits are efficiently distributed among the sub-vectors by allocating a larger fraction of the available bits to the more important sub-vectors and hence maximizing recognition accuracy. The proposed bit-allocation algorithm is based on a novel mutual information (MI) measure …

Date

2004

Authors

Naveen Srinivasamurthy, Antonio Ortega, Shrikanth Narayanan

Conference

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

Volume

1

Pages

I-485

Publisher

IEEE