• 제목/요약/키워드: Continuous Speech Recognition

검색결과 224건 처리시간 0.021초

구문 분석과 One-Stage DMS/DP를 이용한 연속음 인식 (Continuous Speech Recognition using Syntactic Analysis and One-Stage DMS/DP)

  • 안태옥
    • 대한전자공학회논문지SP
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    • 제41권3호
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    • pp.201-207
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    • 2004
  • 본 논문은 연속음 인식에 관한 연구로써, 구문 분석을 이용한 One-Stage DMS/DP에 의한 음성 인식 방법을 사용한다. 인식 실험을 위해 우선 구간 구분화 알고리즘을 이용하여 DMS(dynamic Multi-Section) 모델을 만들며, 구문 분석을 이용한 One-Stage DMS/DP 방법으로 연속음 데이터를 인식하게 하였다. 제안된 방법에 의한 인식 실험을 수행하는 것 외에도 비교를 위해 전통적인 One-Stage DP 방법을 같은 조건 같은 데이터를 가지고 수행하였다. 인식 실험 결과, 기존의 방법보다 구문분석을 이용한 One-Stage DMS/DP 방법이 우수한 것으로 나타났다.

음운 현상과 연속 발화에서의 단어 인지 - 종성중화 작용을 중심으로 (Phonological Process and Word Recognition in Continuous Speech: Evidence from Coda-neutralization)

  • 김선미;남기춘
    • 말소리와 음성과학
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    • 제2권2호
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    • pp.17-25
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    • 2010
  • This study explores whether Koreans exploit their native coda-neutralization process when recognizing words in Korean continuous speech. According to the phonological rules in Korean, coda-neutralization process must come before the liaison process, as long as the latter(i.e. liaison process) occurs between 'words', which results in liaison-consonants being coda-neutralized ones such as /b/, /d/, or /g/, rather than non-neutralized ones like /p/, /t/, /k/, /ʧ/, /ʤ/, or /s/. Consequently, if Korean listeners use their native coda-neutralization rules when processing speech input, word recognition will be hampered when non-neutralized consonants precede vowel-initial targets. Word-spotting and word-monitoring tasks were conducted in Experiment 1 and 2, respectively. In both experiments, listeners recognized words faster and more accurately when vowel-initial target words were preceded by coda-neutralized consonants than when preceded by coda non-neutralized ones. The results show that Korean listeners exploit the coda-neutralization process when processing their native spoken language.

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Recognition of Emotion and Emotional Speech Based on Prosodic Processing

  • Kim, Sung-Ill
    • The Journal of the Acoustical Society of Korea
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    • 제23권3E호
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    • pp.85-90
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    • 2004
  • This paper presents two kinds of new approaches, one of which is concerned with recognition of emotional speech such as anger, happiness, normal, sadness, or surprise. The other is concerned with emotion recognition in speech. For the proposed speech recognition system handling human speech with emotional states, total nine kinds of prosodic features were first extracted and then given to prosodic identifier. In evaluation, the recognition results on emotional speech showed that the rates using proposed method increased more greatly than the existing speech recognizer. For recognition of emotion, on the other hands, four kinds of prosodic parameters such as pitch, energy, and their derivatives were proposed, that were then trained by discrete duration continuous hidden Markov models(DDCHMM) for recognition. In this approach, the emotional models were adapted by specific speaker's speech, using maximum a posteriori(MAP) estimation. In evaluation, the recognition results on emotional states showed that the rates on the vocal emotions gradually increased with an increase of adaptation sample number.

한국어 연속음성에서의 조사 및 어미 인식에 관한 연구 (A Study on Recognition of Korean Postpositions and Suffixes in Continuous Speech)

  • 송민석;이기영
    • 음성과학
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    • 제6권
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    • pp.181-195
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    • 1999
  • This study proposes a method of recognizing postpositions and suffixes in Korean spoken language, using prosodic information. We detect grammatical boundaries automatically at first, by using prosodic information of the accentual phrase, and then we recognize grammatical function words by backward-tracking from the boundaries. The experiment employs 300 sentential speech data of 10 men's and 5 women's voice spoken in standard Korean, in which 1080 accentual phrases and 11 postpositions and suffixes are included. The result shows the recognition rate of postpositions in two cases. In one case in which only correctly detected boundaries are included, the recognition rate is 97.5%, and in the other case in which all detected boundaries are included, the recognition rate is 74.8%.

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Landmark-Guided Segmental Speech Decoding for Continuous Mandarin Speech Recognition

  • Chao, Hao;Song, Cheng
    • Journal of Information Processing Systems
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    • 제12권3호
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    • pp.410-421
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    • 2016
  • In this paper, we propose a framework that attempts to incorporate landmarks into a segment-based Mandarin speech recognition system. In this method, landmarks provide boundary information and phonetic class information, and the information is used to direct the decoding process. To prove the validity of this method, two kinds of landmarks that can be reliably detected are used to direct the decoding process of a segment model (SM) based Mandarin LVCSR (large vocabulary continuous speech recognition) system. The results of our experiment show that about 30% decoding time can be saved without an obvious decrease in recognition accuracy. Thus, the potential of our method is demonstrated.

GMM을 이용한 프레임 단위 분류에 의한 우리말 음성의 분할과 인식 (Korean Speech Segmentation and Recognition by Frame Classification via GMM)

  • 권호민;한학용;고시영;허강인
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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    • pp.18-21
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    • 2003
  • In general it has been considered to be the difficult problem that we divide continuous speech into short interval with having identical phoneme quality. In this paper we used Gaussian Mixture Model (GMM) related to probability density to divide speech into phonemes, an initial, medial, and final sound. From them we peformed continuous speech recognition. Decision boundary of phonemes is determined by algorithm with maximum frequency in a short interval. Recognition process is performed by Continuous Hidden Markov Model(CHMM), and we compared it with another phoneme divided by eye-measurement. For the experiments result we confirmed that the method we presented is relatively superior in auto-segmentation in korean speech.

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시간 동기 비터비 빔 탐색을 위한 인식 시간 감축법 (Recognition Time Reduction Technique for the Time-synchronous Viterbi Beam Search)

  • 이강성
    • 한국음향학회지
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    • 제20권6호
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    • pp.46-50
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    • 2001
  • 본 논문은 HMM (Hidden Markov Model) 음성 인식 시스템에 적용할 수 있는 새로운 인식 시간 알고리즘인 스코아 캐쉬기법을 제안한다. 다른 많은 기법들이 인식 시간을 줄이면서 계산량을 줄이기 위하여 어느 정도의 인식율 저하를 감수하는 반면에 제안하는 스코아 캐쉬기법은 인식율 저하를 전혀 일으키지 않으면서 인식 시간을 상당량 줄일 수 있는 기법이다. 단독어 인식 시스템에 적용 가능할 뿐 아니라 연속어 인식에도 적용이 가능하며, 기존에 이미 설계된 인식 시스템의 구조를 전혀 흩트리지 않고 간단히 하나의 함수만 대치함으로서 인식시간을 크게 감축할 수 있다 또한 기존의 계산량 감축 알고리즘과 함께 적용 가능하므로 추가의 계산량 감소를 얻을 수 있다. 스코아 캐쉬 기법을 적용한 결과 최대 54% 만큼 계산량을 줄일 수 있었다.

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연속음성인식을 위한 음성구간과 피치검출에 관한 연구 (A Study on Speech Period and Pitch Detection for Continuous Speech Recognition)

  • 김태석;장종칠
    • 한국멀티미디어학회논문지
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    • 제8권1호
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    • pp.56-61
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    • 2005
  • 본 논문은 연속음성인식을 위한 음성구간과 피치를 검출하는 알고리즘을 제안한다. 이것은 연속음성을 입력받아 프레임 단위로 자/모음을 구분하며, 구분된 유성음에서 피치를 검출하는 방법이다 실제 잡음 환경에서 음성을 입력받아 적당한 문턱치 에너지를 사용함으로써 잡음환경에서 강인한 음성구간 추출이 가능하였고 추출한 음성구간에서 프레임단위로 영교차율과 단구간에너지를 이용한 알고리즘으로 유성음의 피치를 검출함과 동시에 자/모음을 구분하는 개선된 방식이다.

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자동차 잡음 및 오디오 출력신호가 존재하는 자동차 실내 환경에서의 강인한 음성인식 (Robust Speech Recognition in the Car Interior Environment having Car Noise and Audio Output)

  • 박철호;배재철;배건성
    • 대한음성학회지:말소리
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    • 제62호
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    • pp.85-96
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    • 2007
  • In this paper, we carried out recognition experiments for noisy speech having various levels of car noise and output of an audio system using the speech interface. The speech interface consists of three parts: pre-processing, acoustic echo canceller, post-processing. First, a high pass filter is employed as a pre-processing part to remove some engine noises. Then, an echo canceller implemented by using an FIR-type filter with an NLMS adaptive algorithm is used to remove the music or speech coming from the audio system in a car. As a last part, the MMSE-STSA based speech enhancement method is applied to the out of the echo canceller to remove the residual noise further. For recognition experiments, we generated test signals by adding music to the car noisy speech from Aurora 2 database. The HTK-based continuous HMM system is constructed for a recognition system. Experimental results show that the proposed speech interface is very promising for robust speech recognition in a noisy car environment.

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연속음에서의 각 음소의 대표구간 추출에 관한 연구 (A study on extraction of the frames representing each phoneme in continuous speech)

  • 박찬응;이쾌희
    • 전자공학회논문지B
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    • 제33B권4호
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    • pp.174-182
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    • 1996
  • In continuous speech recognition system, it is possible to implement the system which can handle unlimited number of words by using limited number of phonetic units such as phonemes. Dividing continuous speech into the string of tems of phonemes prior to recognition process can lower the complexity of the system. But because of the coarticulations between neiboring phonemes, it is very difficult ot extract exactly their boundaries. In this paper, we propose the algorithm ot extract short terms which can represent each phonemes instead of extracting their boundaries. The short terms of lower spectral change and higher spectral chang eare detcted. Then phoneme changes are detected using distance measure with this lower spectral change terms, and hgher spectral change terms are regarded as transition terms or short phoneme terms. Finally lower spectral change terms and the mid-term of higher spectral change terms are regarded s the represent each phonemes. The cepstral coefficients and weighted cepstral distance are used for speech feature and measuring the distance because of less computational complexity, and the speech data used in this experimetn was recoreded at silent and ordinary in-dorr environment. Through the experimental results, the proposed algorithm showed higher performance with less computational complexity comparing with the conventional segmetnation algorithms and it can be applied usefully in phoneme-based continuous speech recognition.

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