• Title/Summary/Keyword: VCCV recognition unit

Search Result 7, Processing Time 0.018 seconds

An Implementation of the Vocabulary Independent Speech Recognition System Using VCCV Unit (VCCV단위를 이용한 어휘독립 음성인식 시스템의 구현)

  • 윤재선;홍광석
    • The Journal of the Acoustical Society of Korea
    • /
    • v.21 no.2
    • /
    • pp.160-166
    • /
    • 2002
  • In this paper, we implement a new vocabulary-independent speech recognition system that uses CV, VCCV, VC recognition unit. Since these recognition units are extracted in the trowel region of syllable, the segmentation is easy and robust. And in the case of not existing VCCV unit, the units are replaced by combining VC and CV semi-syllable model. Clustering of vowel group and applying combination rule to the substitution model in the case of not existing of VCCV model lead to 5.2% recognition performance improvement from 90.4% (Model A) to 95.6% (Model C) in the first candidate. The recognition results that is 98.8% recognition rate in the second candidate confirm the effectiveness of the proposed method.

A Language Model based on VCCV of Sentence Speech Recognition (문장 음성 인식을 위한 VCCV기반의 언어 모델)

  • 박선희;홍광석
    • Proceedings of the IEEK Conference
    • /
    • 2003.07e
    • /
    • pp.2419-2422
    • /
    • 2003
  • To improve performance of sentence speech recognition systems, we need to consider perplexity of language model and the number of words of dictionary for increasing vocabulary size. In this paper, we propose a language model of VCCV units for sentence speech recognition. For this, we choose VCCV units as a processing units of language model and compare it with clauses and morphemes. Clauses and morphemes have many vocabulary and high perplexity. But VCCV units have small lexicon size and limited vocabulary. An advantage of VCCV units is low perplexity. This paper made language model using bigram about given text. We calculated perplexity of each language processing unit. The perplexity of VCCV units is lower than morpheme and clause.

  • PDF

Efficient Language Model based on VCCV unit for Sentence Speech Recognition (문장음성인식을 위한 VCCV 기반의 효율적인 언어모델)

  • Park, Seon-Hui;No, Yong-Wan;Hong, Gwang-Seok
    • Proceedings of the KIEE Conference
    • /
    • 2003.11c
    • /
    • pp.836-839
    • /
    • 2003
  • In this paper, we implement a language model by a bigram and evaluate proper smoothing technique for unit of low perplexity. Word, morpheme, clause units are widely used as a language processing unit of the language model. We propose VCCV units which have more small vocabulary than morpheme and clauses units. We compare the VCCV units with the clause and the morpheme units using the perplexity. The most common metric for evaluating a language model is the probability that the model assigns the derivative measures of perplexity. Smoothing used to estimate probabilities when there are insufficient data to estimate probabilities accurately. In this paper, we constructed the N-grams of the VCCV units with low perplexity and tested the language model using Katz, Witten-Bell, absolute, modified Kneser-Ney smoothing and so on. In the experiment results, the modified Kneser-Ney smoothing is tested proper smoothing technique for VCCV units.

  • PDF

Language Model based on VCCV and Test of Smoothing Techniques for Sentence Speech Recognition (문장음성인식을 위한 VCCV 기반의 언어모델과 Smoothing 기법 평가)

  • Park, Seon-Hee;Roh, Yong-Wan;Hong, Kwang-Seok
    • The KIPS Transactions:PartB
    • /
    • v.11B no.2
    • /
    • pp.241-246
    • /
    • 2004
  • In this paper, we propose VCCV units as a processing unit of language model and compare them with clauses and morphemes of existing processing units. Clauses and morphemes have many vocabulary and high perplexity. But VCCV units have low perplexity because of the small lexicon and the limited vocabulary. The construction of language models needs an issue of the smoothing. The smoothing technique used to better estimate probabilities when there is an insufficient data to estimate probabilities accurately. This paper made a language model of morphemes, clauses and VCCV units and calculated their perplexity. The perplexity of VCCV units is lower than morphemes and clauses units. We constructed the N-grams of VCCV units with low perplexity and tested the language model using Katz, absolute, modified Kneser-Ney smoothing and so on. In the experiment results, the modified Kneser-Ney smoothing is tested proper smoothing technique for VCCV units.

A Continuous Digits Speech Recognition Applied Vowel Sequence and VCCV Unit HMM (모음열과 VCCV단위 HMM을 이용한 연속 숫자 음성인식)

  • Youn Jeh-Seon;Chung Kwang-Woo;Hong Kwang-Seok
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • autumn
    • /
    • pp.25-28
    • /
    • 2001
  • 본 논문에서는 조음 효과에 대처할 수 있는 반음절, 반음절 + 반음절 단위 HMM과 모음열 정보를 적용하여 연속 숫자 음성인식을 구현하였다. 모음열 정보를 적용하여 기준모델을 모음이 포함된 HMM단위로만 구성한 시스템과 모든 기준모델과 비교하는 시스템과 성능을 비교하였다. 인식실험결과 인식률의 향상으로 제안된 방법이 효율적임을 확인하였다.

  • PDF

Connected Korean Digit Speech Recognition Using Vowel String and Number of Syllables (음절수와 모음 열을 이용한 한국어 연결 숫자 음성인식)

  • Youn, Jeh-Seon;Hong, Kwang-Seok
    • The KIPS Transactions:PartA
    • /
    • v.10A no.1
    • /
    • pp.1-6
    • /
    • 2003
  • In this paper, we present a new Korean connected digit recognition based on vowel string and number of syllables. There are two steps to reduce digit candidates. The first one is to determine the number and interval of digit. Once the number and interval of digit are determined, the second is to recognize the vowel string in the digit string. The digit candidates according to vowel string are recognized based on CV (consonant vowel), VCCV and VC unit HMM. The proposed method can cope effectively with the coarticulation effects and recognize the connected digit speech very well.

An Utterance Verification using Vowel String (모음 열을 이용한 발화 검증)

  • 유일수;노용완;홍광석
    • Proceedings of the Korea Institute of Convergence Signal Processing
    • /
    • 2003.06a
    • /
    • pp.46-49
    • /
    • 2003
  • The use of confidence measures for word/utterance verification has become art essential component of any speech input application. Confidence measures have applications to a number of problems such as rejection of incorrect hypotheses, speaker adaptation, or adaptive modification of the hypothesis score during search in continuous speech recognition. In this paper, we present a new utterance verification method using vowel string. Using subword HMMs of VCCV unit, we create anti-models which include vowel string in hypothesis words. The experiment results show that the utterance verification rate of the proposed method is about 79.5%.

  • PDF