libTLK
1.3.1
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Functions | |
tL_vtrainer_free (tLVTrainer *vtrainer) | |
Frees memory. | |
tL_vtrainer_new (const tLAModel *amodel, tLAMiCounts *counts, const tLSeqs *seqs, char **err) | |
Gets a tLVTrainer. | |
tL_vtrain (tLVTrainer *vtrainer, const tLFea *fea, const size_t seq) | |
Updates acoustic model counts according to the Viterbi algorithm. |
Updates acoustic model counts according to the Viterbi algorithm.
This function increases the acoustic model's counts, which are stored in the trainer, from one sample (feature vector sequence) and its transcription, using the Viterbi algorithm in order to obtain the integer counts. The sequence is specified as an integer code according to the sequence manager used during the creation of the viterbi trainer.
vtrainer | The viterbi trainer. |
fea | A feature vector manager, which must contain a sequence of feature vectors of an adequate type for the amodel. |
seq | The code of the transcription of the sample. |
tL_vtrainer_free | ( | tLVTrainer * | vtrainer | ) |
Frees memory.
Frees the memory allocated for the auxiliary data.
vtrainer | The Viterbi trainer. |
tL_vtrainer_new | ( | const tLAModel * | amodel, |
tLAMiCounts * | counts, | ||
const tLSeqs * | seqs, | ||
char ** | err | ||
) |
Gets a tLVTrainer.
This function creates auxiliary data used to train an acoustic model from transcriptions using the Viterbi algorithm. This data can only be used to train the symbol sequences stored in seqs during the creation of the trainer. Currently supported types are: Bernoulli, DGaussian and Mixture.
amodel | The acoustic model. |
counts | The integer counts which will be increased. |
seqs | A symbol sequence manager containing the symbol sequences which can be used to train samples. |
err | Pointer to string variable. If not NULL, an error message is allocated in the variable in case of error. |