• Title/Summary/Keyword: PARCOR

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A PARCOR-type DTMF Receiver Feasible in In-band Signalling

  • Gyeong, Mun-Geon;Baek, Je-In;Lee, Yeong-Ho
    • ETRI Journal
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    • v.9 no.3
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    • pp.74-85
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    • 1987
  • In this paper, a new kind of dual tone multifrequency receiver(DTMFR) is proposed, in which detection is made in terms of the partial correlation(PARCOR) coefficients for efficient DTMF signal detection against both temporary decoding errors by crosstalks possibly coming from adjoint telephone lines during transmission and so-called digit simulation by background voice or noise signals during interdigit period. A simulation study on the behaviour of PARCOR coefficients for tone signals and non-signals has been performed in order to provide the rationale on the feasibility of the proposed DTMFR algorithm. Based upon simulation results, a more refined detection strategy as an example is presented and explained together with the corresponding decision logic.

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Design and Implementation of Simple Text-to-Speech System using Phoneme Units (음소단위를 이용한 소규모 문자-음성 변환 시스템의 설계 및 구현)

  • Park, Ae-Hee;Yang, Jin-Woo;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.3
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    • pp.49-60
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    • 1995
  • This paper is a study on the design and implementation of the Korean Text-to-Speech system which is used for a small and simple system. In this paper, a parameter synthesis method is chosen for speech syntheiss method, we use PARCOR(PARtial autoCORrelation) coefficient which is one of the LPC analysis. And we use phoneme for synthesis unit which is the basic unit for speech synthesis. We use PARCOR, pitch, amplitude as synthesis parameter of voice, we use residual signal, PARCOR coefficients as synthesis parameter of unvoice. In this paper, we could obtain the 60% intelligibility by using the residual signal as excitation signal of unvoiced sound. The result of synthesis experiment, synthesis of a word unit is available. The controlling of phoneme duration is necessary for synthesizing of a sentence unit. For setting up the synthesis system, PC 486, a 70[Hz]-4.5[KHz] band pass filter for speech input/output, amplifier, and TMS320C30 DSP board was used.

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Spoken digit recognition Using the ZCR and PARCOR Coefficient (ZCR과 PARCOR 계수를 이용한 숫자음성 인식)

  • 김학윤
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1985.10a
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    • pp.75-78
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    • 1985
  • 본 연구는 시간 영역의 parament를 이용하여 한국어 숫자음(영, 일, 이, 삼, 사, 오, 육, 칠, 팔, 구)을 인식했다. 입력 음성 신호 X(n)의 Beginning Point와 Ending point를 ZCR(Zero-crossing Rate), Magnitude, Energy, Autocorrelation을 이용 Beginning point와 Ending point를 구하고 자음부의 인식은 위 계수들을 이용하여 행했다. 또, 유성음 부분에서는 PARCOR(Partial Autocorrelation), LPC(Linear Predictive Coding)를 이용 모음부와 유성자음을 인식하여 모음을 6개 부류(ㅏ, ㅑ, ㅗ, ㅜ, ㅠ, ㅣ)로 구분 인식했다. 이 방법에 의하면 입력 음성 신호 X(n)의 B.P(Beginning Point)와 E.P(Ending Point)를 쉽게 추출 가능하며 또한 각 Parameter를 이용하여 94.4%의 인식율을 얻었다.

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A study on the automatic recognition of Korean vowel (한국어 단모음 자동 인식에 관한 연구)

  • 안동순
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1984.12a
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    • pp.57-61
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    • 1984
  • In this study, the system is proposed which can be used for recognition of Koean single vowles "ㅏ, ㅓ, ㅗ, ㅜ, ㅡ, ㅣ, ㅐ, ㅔ, ㅚ,", and automatic recognition is processed using $\mu$-computer. 3 men of not-being-studied are participated in this experiment. Using the period of vowels, one part of the steady state is selected for high speed recognition, and amplitude comparison method, LPC, PARCOR, and Formant are used for parameter of recognition. Formant is obtained by peak picking method using LPC, and then vowels are recognized by amplitude comparison method, LPC, PARCOR, and Formant. As a result, Recognition rates are 90.1% for amplitude comparison method, 93.1% for LPC, 100% for PARCOR, 88.8% for using formant.

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On Implementing the Digital DTMF Receiver Using PARCOR Analysis Method (PARCOR 분석 방법에 의한 디지털 DTMF 수신기 구현에 관한 연구)

  • Ha, Pan Bong;ANN, Souguil
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.2
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    • pp.196-200
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    • 1987
  • The following methods are proposed for implementing digital dual tone multi-frequency (DTMF) receiver: using infinite impulse response(IIR) digital filters, period-counting algorithm, discrete Fourier transform(DFT), and fast Fourier transform(FFT)[2]. The PARCOR(Partical Correlation) analysis method which has been widly used in the speech signal processing area is applied to the dual tone multi-frequency(DTMF) signal detection. This method is easy to implement digitally and stronger to digit simulation of speech than any other methods proposed up to date. Since sampling rate of 4KHz is used in the DTMF receiver for the detection of input DTMF signal originally sampled at 8KHz, it effects two times higher multiplexing efficiency.

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The Speech Recognition Method by Perceptual Linear Predictive Analysis (인지 선형 예측 분석에 의한 음성 인식 방법)

  • 김현철
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1995.06a
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    • pp.184-187
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    • 1995
  • This paper proposes an algorithm for machine recognition of phonemes in continuous speech. The proposed algorithm is static strategy neural network. The algorithm uses, at the stage of training neuron, features such as PARCOR coefficient and auditory-like perceptual liner prediction . These features are extracted from speech samples selected by a sliding 25.6msec windows with s sliding gap being 3 msec long, then interleaved and summed up to 7 sets of parmeters covering 171 msec worth of speech for use of neural inputs. Perfomances are compared when either PARCOR or auditory-like PLP is included in the feture set.

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Automatic Vowel Sequence Reproduction for a Talking Robot Based on PARCOR Coefficient Template Matching

  • Vo, Nhu Thanh;Sawada, Hideyuki
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.3
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    • pp.215-221
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    • 2016
  • This paper describes an automatic vowel sequence reproduction system for a talking robot built to reproduce the human voice based on the working behavior of the human articulatory system. A sound analysis system is developed to record a sentence spoken by a human (mainly vowel sequences in the Japanese language) and to then analyze that sentence to give the correct command packet so the talking robot can repeat it. An algorithm based on a short-time energy method is developed to separate and count sound phonemes. A matching template using partial correlation coefficients (PARCOR) is applied to detect a voice in the talking robot's database similar to the spoken voice. Combining the sound separation and counting the result with the detection of vowels in human speech, the talking robot can reproduce a vowel sequence similar to the one spoken by the human. Two tests to verify the working behavior of the robot are performed. The results of the tests indicate that the robot can repeat a sequence of vowels spoken by a human with an average success rate of more than 60%.

Implementation and Performance Analysis of a Speaker Verification System (화자 확인 시스템의 설계 제작 및 성능 분석)

  • 권석규;이병기
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.3
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    • pp.1-9
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    • 1993
  • This paper discusses issues on the disign and implementation of real-time automatic speaker verification system, as well as the performance analysis of the implemented system. The system employs TI's TMS320C25 digital signal processor TMS320C25 and high speed SRAMs. The system is designed to be used stand-alone as well as via hand-shaking with IBM-PC. The speech parameters used for speaker verification are PARCOR and LPC-cepstrum coefficients, and the employed decision logics are those based on the generalized weighted distance comcept. The implemented system showed the performance of 5.3% error rate for the PARCOR coefficient, and 4.7% error rate for the LPG-cepstrum coefficient.

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