Publication detail

Towards Lower Error Rates in Phoneme Recognition

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

Original Title

Towards Lower Error Rates in Phoneme Recognition

English Title

Towards Lower Error Rates in Phoneme Recognition

Type

journal article - other

Language

en

Original Abstract

We investigate techniques for acoustic modeling in automatic recognition of context-independent phoneme strings from the TIMIT database. The baseline phoneme recognizer is based on TempoRAl Patterns (TRAP). This recognizer is simplified to shorten processing times and reduce computational requirements. More states per phoneme and bi-gram language models are incorporated into the system and evaluated. The question of insufficient amount of training data is discussed and the system is improved. All modifications lead to a faster system with about 23.6% relative improvement over the baseline in phoneme error rate.

English abstract

We investigate techniques for acoustic modeling in automatic recognition of context-independent phoneme strings from the TIMIT database. The baseline phoneme recognizer is based on TempoRAl Patterns (TRAP). This recognizer is simplified to shorten processing times and reduce computational requirements. More states per phoneme and bi-gram language models are incorporated into the system and evaluated. The question of insufficient amount of training data is discussed and the system is improved. All modifications lead to a faster system with about 23.6% relative improvement over the baseline in phoneme error rate.

Keywords

phoneme recognition, traps, speech recognition, feature extraction

RIV year

2004

Released

08.09.2004

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Year of study

2004

Number

3206

State

DE

Pages from

465

Pages to

472

Pages count

8

URL

Documents

BibTex


@article{BUT45739,
  author="Petr {Schwarz} and Pavel {Matějka} and Jan {Černocký}",
  title="Towards Lower Error Rates in Phoneme Recognition",
  annote="We investigate techniques for acoustic modeling in automatic
recognition of context-independent phoneme strings from the TIMIT
database. The baseline phoneme recognizer is based on TempoRAl Patterns
(TRAP). This recognizer is simplified to shorten processing times and
reduce computational requirements. More states per phoneme and bi-gram
language models are incorporated into the system and evaluated. The
question of insufficient amount of training data is discussed and the
system is improved. All modifications lead to a faster system with
about 23.6% relative improvement over the baseline in phoneme error
rate.",
  chapter="45739",
  journal="Lecture Notes in Computer Science",
  number="3206",
  volume="2004",
  year="2004",
  month="september",
  pages="465",
  type="journal article - other"
}