Detail publikace

Recognition of Phoneme Strings using TRAP Technique

SCHWARZ, P., MATĚJKA, P., ČERNOCKÝ, J.

Originální název

Recognition of Phoneme Strings using TRAP Technique

Anglický název

Recognition of Phoneme Strings using TRAP Technique

Jazyk

en

Originální abstrakt

We investigate and compare several techniques for automatic recognition of unconstrained context-independent phoneme strings from TIMIT and NTIMIT databases. Among the compared techniques, the technique based on TempoRAl Patterns (TRAP) achieves the best results in the clean speech, it achieves about 10% relative improovements against baseline system. Its advantage is also observed in the presence of mismatch between training and testing conditions. Issues such as the optimal length of temporal patterns in the TRAP technique and the effectiveness of mean and variance normalization of the patterns and the multi-band input the TRAP estimations, are also explored.

Anglický abstrakt

We investigate and compare several techniques for automatic recognition of unconstrained context-independent phoneme strings from TIMIT and NTIMIT databases. Among the compared techniques, the technique based on TempoRAl Patterns (TRAP) achieves the best results in the clean speech, it achieves about 10% relative improovements against baseline system. Its advantage is also observed in the presence of mismatch between training and testing conditions. Issues such as the optimal length of temporal patterns in the TRAP technique and the effectiveness of mean and variance normalization of the patterns and the multi-band input the TRAP estimations, are also explored.

Dokumenty

BibTex


@inproceedings{BUT14174,
  author="Petr {Schwarz} and Pavel {Matějka} and Jan {Černocký}",
  title="Recognition of Phoneme Strings using TRAP Technique",
  annote="We investigate and compare several techniques for automatic recognition
of unconstrained context-independent phoneme strings from TIMIT and
NTIMIT databases. Among the compared techniques, the technique based on
TempoRAl Patterns (TRAP) achieves the best results in the clean speech,
it achieves about 10% relative improovements against baseline system.
Its advantage is also observed in the presence of mismatch between
training and testing conditions. Issues such as the optimal length of
temporal patterns in the TRAP technique and the effectiveness of mean
and variance normalization of the patterns and the multi-band input the
TRAP estimations, are also explored.",
  address="International Speech Communication Association",
  booktitle="Proceedings of 8th International Conference Eurospeech",
  chapter="14174",
  institution="International Speech Communication Association",
  journal="5th European Conference EUROSPEECH 97",
  number="9",
  year="2003",
  month="june",
  pages="1--4",
  publisher="International Speech Communication Association",
  type="conference paper"
}