• Speech Sciences
• /
• v.3
• /
• pp.26-37
• /
• 1998

The Connected Speech Test (CST) was developed to test hearing aid performance using realistic stimuli (Connected speech) presented in a background of noise with a visible speaker. The CST has not been investigated as a measure of speech reading ability using the visual portion of the CST only. Thirty subjects were administered the 48 test lists of the CST using visual presentation mode only. Statistically significant differences were found between the 48 test lists and between the 12 passages of the CST (48 passages divided into 12 groups of 4 lists which were averaged.). No significant differences were found between male and female subjects; however, in all but one case, females scored better than males. No significant differences were found between students in communication disorders and students in other departments. Intra- and inter-subject variability across test lists and passages was high. Suggestions for further research include changing the scoring of the CST to be more contextually based and changing the speaker for the CST.

• Phonetics and Speech Sciences
• /
• v.3 no.4
• /
• pp.109-115
• /
• 2011

The purposes of this study were to identify acoustic parameters of connected speech and to contribute to acoustic analysis of dysphonic voice about patient's natural speech voice as well as sustained phonation of vowels. Acoustic parameters of sentences included LTAS (long-term average spectrum) mean and spectral slope over frequence ranges such as 0-4kHz, 0-6kHz, 0-8kHz, 0-12.5kHz as well as HNR. Acoustic parameters of the vowel 'a' included jitter, RAP, shimmer, NHR, and HNR. Based on 'G' of GRBAS for the severity of dysphonia, two experienced raters judged and classified as four groups including controls, mild, moderate and severe dysphonic group. Connected speech was two sentences extracted from 'stroll' passage. Parameters of the vowel and LTAS mean of the sentences were measured by CSL. The spectral slope of the sentences and HNR of the vowel and the sentences were measured by Praat. Data were statistically analyzed by Spearman correlation and Kruskal-Wallis test using SPSS 12.0. The results of this study are as follows: First, jitter, RAP, shimmer and NHR were significantly different between the groups. Second, for several frequencies, LTAS mean and spectral slope of the sentences were significantly different between the groups. Third, the HNR of the sentences were significantly different between the groups. Forth, there was a presence of correlation between HNR and NHR of the vowel and HNR of the sentences. Accordingly, this study concluded that LTAS, spectral slope, and HNR were predictive parameters of connected speech voice for dysphonic voice.

• Journal of the Korea Convergence Society
• /
• v.9 no.6
• /
• pp.125-132
• /
• 2018

This study was to investigate the speech sound production characteristics and evaluation aspects of preschool children through word test and connected speech test. For this, the authors conducted Assessment of Phonology and Articulation for Children(APAC) to 72 normal children(24 three-, four-, and five-year-olds each) and analyzed difference in percent of correct consonant(PCC) and intelligibility according to age and sex, correlation between PCC and intelligibility, and speech sound error patterns. PCC and intelligibility increased with age but there was no difference according to sex. The correlation was statistically significant in 5-year-old group. Speech sound error patterns were different in the two tests. This study showed that children's speech sound production varied according to language unit. Therefore, both types of tests should be done to grasp their speech sound production ability properly. This suggests that current standard to identify language impairment only by PCC of word level requires review and further studies.

• Phonetics and Speech Sciences
• /
• v.3 no.3
• /
• pp.149-155
• /
• 2011

The purpose of the present study was to identify the differences in GRBAS scales between vocal sample types (sustained vowels and connected speech) for specific laryngeal conditions (vocal nodules, vocal polyps and vocal paralysis) and the relations between GRBAS scale and Shimmer value in each vocal sample type. In this study, the total of 60 voice samples of 30 patients (10 vocal nodules, 10 vocal polyps, 10 vocal paralysis) were examined and MDVP (Multi-dimensional Voice Program) was used to analyze Shimmer value. Three listeners rated two types of samples which were sorted randomly based on GRBAS scale. Three-way ANOVA, one-way ANOVA and paired t-test were used. The outcome of this study was as follow. 1) GRBAS scales varied in vocal sample types. Listeners tended to assess voices as better quality when they listened connected speech rather than sustained vowels. 2) G score of GRBAS and Shimmer were positively correlated with statistical significance. This results show that 1) vocal specialists should consider the sample types in evaluating the severity of voice problem and 2) G score could be a simple and clear method.

• MALSORI
• /
• no.45
• /
• pp.79-91
• /
• 2003

Utterance verification aims at rejecting both out-of-vocabulary (OOV) utterances and low-confidence-scored in-vocabulary (IV) utterances. For utterance verification on Korean connected digit recognition task, we investigate several methods to construct filler and anti-digit models. In particular, we propose a substitution error correction method based on 2-best decoding results. In this method, when 1st candidate is rejected, 2nd candidate is selected if it is accepted by a specific hypothesis test, instead of simply rejecting the 1st one. Experimental results show that the proposed method outperforms the conventional log likelihood ratio (LLR) test method.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.57-64
• /
• 2021

In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.

• MALSORI
• /
• no.49
• /
• pp.77-94
• /
• 2004

In this paper, new voice message system supporting massive outbound call is proposed. Basic idea of the proposed system is to pre-process all the text-to-speech conversion process, mixing of text and attached music file and to store the results of pre-process in the cache server which is connected to the IVR. New voice message system is optimized for the voice message system supporting massive outbound call by distributing the load of the web server caused by server-side script implementation which is accessing database and generating dynamic Voice XML document over client module and server module of web server. The proposed voice message system was test-deployed in one domestic voice message application service provider and it is shown that proposed voice message system reduced the response latency problem of test-bed voice message system.

• Proceedings of the KSPS conference
• /
• 2006.11a
• /
• pp.127-130
• /
• 2006

The purpose of this study is to examine the difference in acoustic features between Young Voices and Aged Voices, which are actually come from the same age group. The 12 female subjects in their thirties were participated and recorded their sustained vowel /a/, connected speech, and reading. Their voices were divided into Younger Voices and Aged Voices, which means voices sound like younger person and sound like in their age or more aged ones. Praat 4.4.22 was used to record and analyze their acoustic features like Fo, SFF, Jitter, Shimmer, HNR, Pitch-range. And the six female listeners guessed the subjects' age and judged whether they sound younger or as like their actual age. We used the Independent t-Test to find the significant difference between those two groups' acoustic features. The result shows a significant difference in Fo, SFF. The above and the previous studies tell us the group who sounds like younger or baby like voice has the similar acoustic features of actually young people.

• Phonetics and Speech Sciences
• /
• v.1 no.1
• /
• pp.93-98
• /
• 2009

The aim of this study was to investigate voice characteristics of adductive spasmodic dysphonia(ADSD) by measuring electroglottal and acoustic examination at the sentence level. The clinical records of 86 ADSD female patients (age group of $20{\sim}50$ years) and the control records of 86 normal females (age group of $20{\sim}40$ years) were recorded by speech studio(Laryngograph Ltd., UK). An independent t-test was used to compare ADSD and normal group. Results were as follows. (1) Fundamental frequency($F_0$) was significantly decreased in ADSD compared with normal group. (2) Irregularity of frequency and closed quotient(CQ) was significantly increased in ADSD compared with normal group. (3) Voiceless duration increased and voiced duration was significantly decreased in ADSD compared with normal group. (4) Fricative duration was increased in ADSD compared with normal group but it wasn't significant. In conclusion, strained, tight and choked voice shows an increase of CQ, tremor voice shows an increase of irregularity of frequency and less feminine voice shows decrease of $F_0$. Increase of voiceless duration and fricative duration and decrease of voiced duration related with diminution speech intelligibility.

• The Journal of the Acoustical Society of Korea
• /
• v.14 no.5
• /
• pp.74-82
• /
• 1995

This paper is study on the voice dialing using HMM and post processing of the connected digits. HMM algorithm is widely used in the speech recognition with a good result. But, the maximum likelihood estimation of HMM(Hidden Markov Model) training in the speech recognition does not lead to values which maximize recognition rate. To solve the problem, we applied the post processing to segmental K-means procedure are in the recognition experiment. Korea connected digits are influenced by the prolongation more than English connected digits. To decrease the segmentation error in the level building algorithm some word models which can be produced by the prolongation are added. Some rules for the added models are applied to the recognition result and it is updated. The recognition system was implemented with DSP board having a TMS320C30 processor and IBM PC. The reference patterns were made by 3 male speakers in the noisy laboratory. The recognition experiment was performed for 21 sort of telephone number, 252 data. The recognition rate was $6\%$ in the speaker dependent, and $80.5\%$ in the speaker independent recognition test.