RESPITE: The CASA Toolkit Page: Documentation: Block Library Index:HMMDecoderMultisource


[Note, this is an experimental decoder that is still under development.]

The `multisource' decoder accepts a 1/0 missing data mask and a mask of integer labels that define grouped regions (`fragments') in the 1/0 mask. These fragments are assumed to be regions of the representation that are due to a single source. Rather than using a single fixed present data mask the decoder attempts to test every mask that can be generated from a subset of the mask fragments. As there is potentially a very large number of mask hypotheses, a limited search is employed. This search proceeds by generating new complimentary hypotheses when a fragment starts and merging partial complementary hypotheses every time a fragment ends. The algorithm is described in more details in:

The multisource decoder has five inputs. The data, mask, group labellings and lower and upper missing data bounds.

The parameters are similar to those of HMMDecoderMD but with the following additions:

Note, the block has two outputs - but these outputs should not be used and will be removed in future releases.

Inputs Meaning Sample 1-D frame $\ge$2-D frame
in1 feature vectors   Yes  
in2 fuzzy data mask   Yes  
in3 group labels   Yes  
(in4) lower bound   Yes  
in5 upper bound   Yes  

Outputs Meaning

Parameters Type Default Meaning
LOG_FILE String - Name of an optional log file
LOG_FILE_2 String - Name of additional detailed log file
WORD_PENALTY Float 0.0 The creation penalty
HMM_FILE String - Name of the HMM file list
GRAMMAR_FILE String - File storing the grammar
LABEL_FILE String - File storing HMM NAME-> HMM LABEL mapping
FIRST_TOKEN String - Label of a fixed first token
FINAL_TOKEN String - Label of a fixed final token
TRANSCRIPTION String - The correct transcription
SILENCE String "" The silence label(s)
MAX_APPROX Boolean False Use max mixture approximation
NBEST Int 1 Return best n hypotheses
STATE_PATH Boolean False Record HMM state path
HAS_DELTAS Boolean 0 Models have delta parameters
USE_DELTAS Boolean - Models have delta parameters
HYPOTHESIS FILTER String "" Regular expression for filtering hypotheses
OUTPUT_CONFUSIONS Boolean 0 Output confusion matrix
DUMP_PARAMETERS Boolean 0 Write parameters to log file
DISPLAY_GROUPS Boolean 0 Display mask backtrace (requires MATLAB)
USE_DELTA_BOUNDS Boolean False Use bounded marginalisation (delta features)
MD_WEIGHT Float 0.0 Balances amount of present/missing data
NORMALISE_MODE {MODE_1, MODE_2} MODE_1 The technique used to balance the amount of present/missing data

Documentation for CTKv1.1.4 - Last modified: Tue Jul 3 13:02:32 BST 2001