• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.2
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• pp.92-97
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• 2004

Background and Objectives : The purpose of this study was to examine objectively pre and post operative voice quality evaluation and intelligibility of alaryngeal voice using speech recognition program, HUVOIS. Materials and Methods : 2 laryngologists and 1 speech pathologist were evaluated 'G', 'R', 'B' in the GRBAS sclae and speech intelligibility using NTID rating scale from standard paragraph. And also acoustic estimates such as jitter, shimmer, HNR were obtained from Lx Speech Studio. Results : Speech recognition rate was not significantly different between pre and post operation for pathological vocie samples though voice quality(G, B) and acoustic values(Jitter, HNR) were significantly improved after post operation. In Alaryngeal voices, reed type electrolarynx 'Moksori' was the highest both speech intelligibility and speech recognition rate, whereas esophageal speech was the lowest. Coefficient correlation of speech intelligibility and speech recognition rate was found in alaryngeal voices, but not in pathological voices. Conclusion : Current study was not proved speech recognition program, HUVOIS during telephone program was not objective and efficient method for assisting subjective GRBAS scale.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.394-400
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• 2002

In digital speech communications, the quality of service can be increased by speech coding scheme that is adaptive to the error rate of voice packet transmission. However, current communication protocol in cellular and internet communications does not provide the function that transmits the channel error information. To solute this problem, in this paper, new method for real-time transmission of channel error information is proposed, where channel error information is embedded in voice packet. The proposed method utilizes the pulse positions of codevector in ACELP speech codec, which results in little degradation in speech quality and low false alarm rate. The simulations with various speech data show that the proposed method meets the requirement in speech quality, detection rate, and false alarm rate.

• Journal of Korean language education
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• v.29 no.4
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• pp.137-168
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• 2018

The purpose of this study is to prepare the basis for a more objective evaluation of oral fluency by comparing speech patterns of Korean native speakers and L2 Korean learners. For this purpose, the current study focused on the analysis of speech materials of the 21st century Sejong spoken corpus and Korean learner corpus. We compared the oral fluency of Korean native speakers and Korean learners based on speech rate, pause, and discourse markers. The results show that the pattern of Korean learners is different to that of Korean native speakers in all aspects of speech rate, pause, and discourse markers; even though proficiency of Korean leaners show increase, they could not reach the oral fluency level of Korean native speakers. At last, based on these results of the analysis, we added suggestions for setting the evaluation criteria of oral fluency of Korean learners.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.273-278
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• 2009

In this paper, we propose the spectral transition rate (STR) as a novel feature for speech and music discrimination (SMD). We observed that the spectral peaks of speech signal are gradually changing due to coarticulation effect. However, the sound of musical instruments in general tends to keep the peak frequencies and energies unchanged for relatively long period of time compared to speech. The STR of speech is much higher than that of music. The experimental results show that the STR based SMD method outperforms a conventional method. Especially, the STR based SMD gives relatively fast output without any performance degradation.

• Speech Sciences
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• v.7 no.2
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• pp.209-224
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• 2000

This paper proposes an automatic detection method of intonational and accentual phrases in Korean standard continuous speech. We use the pause over 150 msec for detecting intonational phrases, and extract accentual phrases from the intonational phrases by analyzing syllables and pitch contours. The speech data for the experiment are composed of seven male voices and two female voices which read the texts of the fable 'the ant and the grasshopper' and a newspaper article 'manmulsang' in normal speed and in Korean standard variation. The results of the experiment shows that the detection rate of intonational phrases is 95% on the average and that of accentual phrases is 73%. This detection rate implies that we can segment the continuous speech into smaller units(i.e. prosodic phrases) by using the prosodic information and so the objects of speech recognition can narrow down to words or phrases in continuous speech.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.276-280
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• 2016

A fixed rate speech coder based on the filter bank and the non-uniform sampling technique is proposed. The non-uniform sampling is achieved by the detection of inflection points (IPs). A speech block is band passed by the filter bank, and the subband signals are processed by the IP detector, and the detected IP patterns are compared with entries of the IP database. For each subband signal, the address of the closest member of the database and the energy of the IP pattern are transmitted through channel. In the receiver, the decoder recovers the subband signals using the received addresses and the energy information, and reconstructs the speech via the filter bank summation. As results, the coder shows fixed data rate contrary to the existing speech coders based on the non-uniform sampling. Through computer simulation, the usefulness of the proposed technique is confirmed. The signal-to-noise ratio (SNR) performance of the proposed method is comparable to that of the uniform sampled pulse code modulation (PCM) below 20 kbps data rate.

• Phonetics and Speech Sciences
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• v.4 no.2
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• pp.121-126
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• 2012

This study deals with how stuttering changes in its frequency in a situation where adult participants who stutter are exposed to one type of background noise, that is, multi-talker babble noise. Eight American English-speaking adults who stutter participated in this study. Each of the subjects read aloud sentences under each of three speaking conditions (i.e., typical solo reading (TSR), typical choral reading (TCR), and multi-talker babble noise reading (BNR)). Speech fluency was computed based on a percentage of syllables stuttered (%SS) and speaking rate was also assessed to examine if there was significant change in rates as a measure of vocal change under each of the speaking conditions. The study found that participants read more fluently both during BNR and during TCR than during TSR. The study also found that participants did not show significant changes in speaking rate across the three speaking conditions. Some discussion was provided in relation to the effect of multi-talker babble noise on the frequency of stuttering and its further speculation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.105-110
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• 2008

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.

• Speech Sciences
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• v.10 no.4
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• pp.117-124
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• 2003

Speaker recognition is the technology that confirms the identification of speaker by using the characteristic of speech. Such technique is classified into speaker identification and speaker verification: The first method discriminates the speaker from the preregistered group and recognize the word, the second verifies the speaker who claims the identification. This method that extracts the information of speaker from the speech and confirms the individual identification becomes one of the most efficient technology as the service via telephone network is popularized. Some problems, however, must be solved for the real application as follows; The first thing is concerning that the safe method is necessary to reject the imposter because the recognition is not performed for the only preregistered customer. The second thing is about the fact that the characteristic of speech is changed as time goes by, So this fact causes the severe degradation of recognition rate and the inconvenience of users as the number of times to utter the text increases. The last thing is relating to the fact that the common characteristic among speakers causes the wrong recognition result. The silence parts being included the center of speech cause that identification rate is decreased. In this paper, to make improvement, We proposed identification rate can be improved by removing silence part before processing identification algorithm. The methods detecting speech area are zero crossing rate, energy of signal detect end point and starting point of the speech and process DTW algorithm by using two methods in this paper. As a result, the proposed method is obtained about 3% of improved recognition rate compare with the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.122-129
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• 2022

In this paper, we propose a method to improve the performance of Transformer-based speech recognizers using data augmentation that locally adjusts the frame rate. First, the start time and length of the part to be augmented in the original voice data are randomly selected. Then, the frame rate of the selected part is changed to a new frame rate by using linear interpolation. Experimental results using the Wall Street Journal and LibriSpeech speech databases showed that the convergence time took longer than the baseline, but the recognition accuracy was improved in most cases. In order to further improve the performance, various parameters such as the length and the speed of the selected parts were optimized. The proposed method was shown to achieve relative performance improvement of 11.8 % and 14.9 % compared with the baseline in the Wall Street Journal and LibriSpeech speech databases, respectively.