• The Journal of the Acoustical Society of Korea
• /
• v.21 no.3
• /
• pp.315-322
• /
• 2002

In this paper, a new temporal decomposition method is proposed. which takes into consideration not only spectral distortion but also bit rates. The interpolation functions, which are one of necessary parameters for temporal decomposition, are obtained from the training speech corpus. Since the interval between the two targets uniquely defines the interpolation function, the interpolation can be represented without additional information. The locations of the targets are determined by minimizing the bit rates while the maximum spectral distortion maintains below a given threshold. The proposed method has been applied to compressing the LSP coefficients which are widely used as a spectral parameter. The results of the simulation show that an average spectral distortion of about 1.4 dB can be achieved at an average bit rate of about 8 bits/Frame.

• The Journal of the Acoustical Society of Korea
• /
• v.9 no.4
• /
• pp.66-76
• /
• 1990

In this work, the effect of noise and distortion of a telephone channel on the speech recognition is studied, and methods to improve the recognition rate are proposed. Computer simulation is done using the 100-word test data whichwere made by pronouncing ten times 100-phonetically balanced Korean isolated words in a speaker dependent mode. First, a spectral subtraction method is suggested to improve the noisy speech recognition. Then, the effect of bandwidth limiting and channel distortion is studied. It has been found that bandwidth limiting and amplitude distortion lower the recognition rate significantly, but phase distortion affects little. To reduce the channel effect, we modify the reference pattern according to some training data. When both channel noise and distortion exist, the recognition rate without the proposed method is merely 7.7~26.4%, but the recognition rate with the proposed method is drastically increased to 76.2~92.3%.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.4
• /
• pp.112-118
• /
• 2010

This paper describes a noise suppression system based on a normalization method using a time-delay neural network and line spectrum pair having a parameter of frequency domain. First, a time-delay neural network is trained using line spectrum pair values of noisy speech signals obtained by linear prediction analysis. After trained the time-delay neural network, the proposed system enhances speech signals that are degraded by a background noise. Accordingly, the proposed time-delay neural network restores from the line spectrum pair values of noisy speech signals to the line spectrum pair values of clean speech signals. It is confirmed that this system is effective for speech signals degraded by a background noise, judging from spectral distortion measurement.

• Journal of Korea Multimedia Society
• /
• v.6 no.3
• /
• pp.462-468
• /
• 2003

In a speech coding system using excitation source of voiced and unvoiced, it would be involved a distortion of speech quality in case coexist with a voiced and an unvoiced consonants in a frame. So, I propose TSIUVC(Transition Segment Including Unvoiced Consonant) searching and extraction method in order to uncoexistent with a voiced and unvoiced consonants in a frame. This paper present a new method of TSIUVC approximate-synthesis by using Least Mean Square and frequency band division. As a result, this method obtain a high quality approximation-synthesis waveforms within TSIUVC by using frequency information of 0.547KHz below and 2.813KHz above. The important thing is that the maximum error signal can be made with low distortion approximation-synthesis waveform within TSIUVC. This method has the capability of being applied to a new speech coding of Voiced/Silence/TSIUVC, speech analysis and speech synthesis.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.2
• /
• pp.167-172
• /
• 2002

The EVRC (Enhanced Variable Rate Codec) is currently in service as a speech cosec in digital cellular systems in North America and Korea. In the EVRC, the LSP (Line Spectral Pairs) related to energy distribution of speech signals in the frequency domain are coded by weighted split vector quantization. Considering that the LSP codebooks might be trained with the language of the develop country of the codebooks or English, it is expected that codebooks trained with Korean provide the performance improvements in the communication in Korean. In this paper, the EVRC LSP codebooks are designed with korean adopting the LBG algorithm based vector quantization, and the performance improvement of the vector quantization and the accompanying speech quality improvement are demonstrated by spectral distortion, SNR and SegSNR measurements, respectively.

• MALSORI
• /
• no.49
• /
• pp.63-75
• /
• 2004

Most existing telephone speech transmitted in current public networks is band-limited to 0.3-3.4 kHz. Compared with wideband speech(0-8 kHz), the narrowband speech lacks low-band (0-0.3 kHz) and high-band(3.4-8 kHz) components of sound. As a result, the speech is characterized by the reduced intelligibility and a muffled quality, and degraded speaker identification. Bandwidth extension is a technique to provide wideband speech quality, which means reconstruction of low-band and high-band components without any additional transmitted information. Our new approach considers to exploit harmonic synthesis method for reconstruction of low-band speech over the CELP coded speech. A spectral distortion measurement and listening test are introduced to assess the proposed method, and the improvement of synthesized speech quality was verified.

• Speech Sciences
• /
• v.7 no.1
• /
• pp.17-29
• /
• 2000

The STC(Sinusoidal Transform Coding) is a vocoding technique that uses a sinusoidal speech model to obtain high- quality speech at low data rate. It models and synthesizes the speech signal with fundamental frequency and its harmonic elements in frequency domain. To reduce the data rate, it is necessary to represent the sinusoidal amplitudes and phases with as small number of peaks as possible while maintaining the speech quality. As a basic research to develop a low-rate speech coding algorithm using the sinusoidal model, in this paper, we investigate the speech quality depending on the number of sinusoids. By varying the number of spectral peaks from 5 to 40 speech signals are reconstructed, and then their qualities are evaluated using spectral envelope distortion measure and MOS(Mean Opinion Score). Two approaches are used to obtain the spectral peaks: one is a conventional STFT (Short-Time Fourier Transform), and the other is a multiresolutional analysis method.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.676-679
• /
• 1999

In this paper, we presents a method to control prosody of the synthetic speech using sampling rate conversion technique. In prosody control, the conventional methods perform overlap and add. So the synthetic speech has a distortion and the voice quality is not satisfied. Using sampling rate conversion technique, we can get high Qualify of the synthetic speech. Also we can control various talking speeds according to speaker's patterns.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.07a
• /
• pp.122-125
• /
• 2011

In real environment, background noise exists everywhere and degrades the performance of system. To reduce this distortion, a speech enhancement algorithm can be very useful and variety methods have been proposed. In this paper, we propose a postfilter to improve the performance of optimally modified log-spectral amplitude (OM-LSA) estimator. Proposed algorithm uses the formant postfilter to minimize perceptual distortion caused by background noise. We adjust an emphasizing parameter which is varied by spectral flatness and first reflection coefficient. The performance of the proposed algorithm is evaluated by measuring the log-spectral distance (LSD) and the perceptual evaluation of speech quality (PESQ) score. The test results show the improvement of proposed algorithm compared to conventional OM-LSA.

• ETRI Journal
• /
• v.38 no.6
• /
• pp.1190-1196
• /
• 2016

We propose a new bandpass filter (BPF)-based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF-based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing