The connected word recognition problem Problem definition: Given a fluently spoken sequence of words, how can we determine the optimum match in terms of a concatenation of word reference patterns?

To solve the connected word recognition problem, we must resolve the following problems

connected word recognition

connected word recognition

connected word recognition

connected word recognition

connected word recognition The alternative algorithms: Two-level dynamic programming approach Level building approach One-stage approach and subsequent generalizations

Two-level dynamic programming algorithm

Two-level dynamic programming algorithm

Two-level dynamic programming algorithm

Two-level dynamic programming algorithm Computation cost of the two-level DP algorithm is: The required storage of the range reduced algorithm is: e.g., for M=300, N=40, V=10, R=5 C=1,320,000 grid points And S=6600 locations for D(b,e)

Level Building algorithm

Computation Of The Level Building Algorithm

Implementation Aspects of Level Building Beginning range reduction – MT Global range reduction – ε Test pattern ending range – δEND Reference pattern uncertainty regions – δR1 , δR2

Integration of a Grammar Network

1 I 5 ONE 9 BOOKS 13 OLD 2 WANT 6 A 10 COAT 3 NEED 7 AN 11 COATS 4 THREE 8 BOOK 12 NEW  

Current Words Predecessor State Uses Level Levels 2 I 1 3 WANT 4 NEED 5 THREE 6 A 7 AN 8 ONE NEW OLD 9 9* BOOK, COAT 10 7,8,9 BOOKS, COATS 11

One-pass or One-state algorithm Also known as frame-synchronous level building (FSLB) method For each test frame the accumulated distance is calculated as:

One-pass or One-state algorithm

One-pass or One-state algorithm

One-pass or One-state algorithm The problem is that no mechanism is provided for Controlling the resulting string path. For incorporating the level, we write:

Incorporating multiple candidate strings

Using HMM in level building

Segmental k-means Training Algorithm