• Journal of Audiology & Otology
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• v.23 no.3
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• pp.121-128
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• 2019

Background and Objectives: There is a scant evidence on the use of simulations in audiology (especially in Malaysia) for case-history taking, although this technique is widely used for training medical and nursing students. Feedback is one of the important components in simulations training; however, it is unknown if feedback by instructors could influence the simulated patient (SP) training outcome for case-history taking among audiology students. Aim of the present study is to determine whether the SP training with feedback in addition to the standard role-play and seminar training is an effective learning tool for audiology case-history taking. Subjects and Methods: Twenty-six second-year undergraduate audiology students participated. A cross-over study design was used. All students initially attended two hours of seminar and role-play sessions. They were then divided into three types of training, 1) SP training (Group A), 2) SP with feedback (Group B), and 3) a non-additional training group (Group C). After two training sessions, the students changed their types of training to, 1) Group A and C: SP training with feedback, and 2) Group B: non-additional training. All the groups were assessed at three points: 1) pre-test, 2) intermediate, and 3) post-test. The normalized median score differences between and within the respective groups were analysed using non-parametric tests at 95% confidence intervals. Results: Groups with additional SP trainings (with and without feedback) showed a significantly higher normalized gain score than no training group (p<0.05). Conclusions: The SP training (with/without feedback) is a beneficial learning tool for history taking to students in audiology major.

• Korean Journal of Audiology
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• v.23 no.3
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• pp.121-128
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• 2019

Background and Objectives: There is a scant evidence on the use of simulations in audiology (especially in Malaysia) for case-history taking, although this technique is widely used for training medical and nursing students. Feedback is one of the important components in simulations training; however, it is unknown if feedback by instructors could influence the simulated patient (SP) training outcome for case-history taking among audiology students. Aim of the present study is to determine whether the SP training with feedback in addition to the standard role-play and seminar training is an effective learning tool for audiology case-history taking. Subjects and Methods: Twenty-six second-year undergraduate audiology students participated. A cross-over study design was used. All students initially attended two hours of seminar and role-play sessions. They were then divided into three types of training, 1) SP training (Group A), 2) SP with feedback (Group B), and 3) a non-additional training group (Group C). After two training sessions, the students changed their types of training to, 1) Group A and C: SP training with feedback, and 2) Group B: non-additional training. All the groups were assessed at three points: 1) pre-test, 2) intermediate, and 3) post-test. The normalized median score differences between and within the respective groups were analysed using non-parametric tests at 95% confidence intervals. Results: Groups with additional SP trainings (with and without feedback) showed a significantly higher normalized gain score than no training group (p<0.05). Conclusions: The SP training (with/without feedback) is a beneficial learning tool for history taking to students in audiology major.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.257-267
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• 2009

This paper presents a training method for neural networks and the employment of MSE (mean scare error) values as the basis of a decision regarding the identity claim of a speaker in a recurrent neural networks based speaker verification system. Recurrent neural networks (RNNs) are employed to capture temporally dynamic characteristics of speech signal. In the process of supervised learning for RNNs, target outputs are automatically generated and the generated target outputs are made to represent the temporal variation of input speech sounds. To increase the capability of discriminating between the true speaker and an impostor, a discriminative training method for RNNs is presented. This paper shows the use and the effectiveness of the MSE value, which is obtained from the Euclidean distance between the target outputs and the outputs of networks for test speech sounds of a speaker, as the basis of speaker verification. In terms of equal error rates, results of experiments, which have been performed using the Korean speech database, show that the proposed speaker verification system exhibits better performance than a conventional hidden Markov model based speaker verification system.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.159-162
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• 2005

Identification is the process automatically identify who is speaking on the basis of information obtained from speech waves. In training phase, each speaker models are trained using each speaker's speech data. GMMs (Gaussian Mixture Models), which have been successfully applied to speaker modeling in text-independent speaker identification, are not efficient in insufficient training data environment. This paper proposes speaker modeling method using MLLR (Maximum Likelihood Linear Regression) method which is used for speaker adaptation in speech recognition. We make SD-like model using MLLR adaptation method instead of speaker dependent model (SD). Proposed system outperforms the GMMs in small training data environment.

• Speech Sciences
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• v.11 no.2
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• pp.51-67
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• 2004

The objective of this study was to investigate the effects in auditory performance and vocal development of Onomatopoeia and Mimetic Word Productive Training Program in prelingually deafened children with cochlear implantation. The effects were measured with Lip-profile (Listening progress profile: LiP), the number of utterances, vocal developmental level and phonetic inventory. Subjects were four children with cochlear implants who were able to detect speech sounds and environmental sounds. The Onomatopoeia and Mimetic word Productive Training Program was made up of 3 steps with 24 Onomatopoeia and Mimetic words. This study was pre and post design. The results of the study were as follows: First, after Onomatopoeia and Mimetic word Productive Training Program was treated, LiP score was significantly higher. Second, after this program was treated, the number of utterances and emergence of both canonical and postcanonical utterances were increased. Emergence of vowel and consonant Features were increased and diversified. In conclusion, Onomatopoeia and Mimetic Word Productive Training Program appeared to facilitate efficient auditory performance and vocal development.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.7 no.1
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• pp.43-49
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• 1996

In this study, remote articulation training system which connects the hearing disabled trainee and the speech therapist via B-ISDN is introduced. The hearing disabled does not have the hearing feedback of his own pronuciation, and the chance of watching his speech organs movement trajectory will offer him the self-training of articulation. So the system has two purposes of self articulation training and trainer's on-line checking in remote place. We estimate the vocal tract articultory movements from the speech signal using inverse modelling and display the movement trajectoy on the sideview of human face graphically. The trajectories of trainees articulation is displayed along with the reference trajectories, so the trainee can control his articulating to make the two trajectories overlapped. For on-line communication and ckecking training record the system has the function of video conferencing and tranferring articulatory data.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.39-48
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• 2018

A typical statistical parametric speech synthesis (text-to-speech, TTS) system consists of separate modules, such as a text analysis module, an acoustic modeling module, and a speech synthesis module. This causes two problems: 1) expert knowledge of each module is required, and 2) errors generated in each module accumulate passing through each module. An end-to-end TTS system could avoid such problems by synthesizing voice signals directly from an input string. In this study, we implemented an end-to-end Korean TTS system using Google's Tacotron, which is an end-to-end TTS system based on a sequence-to-sequence model with attention mechanism. We used 4392 utterances spoken by a Korean female speaker, an amount that corresponds to 37% of the dataset Google used for training Tacotron. Our system obtained mean opinion score (MOS) 2.98 and degradation mean opinion score (DMOS) 3.25. We will discuss the factors which affected training of the system. Experiments demonstrate that the post-processing network needs to be designed considering output language and input characters and that according to the amount of training data, the maximum value of n for n-grams modeled by the encoder should be small enough.

• MALSORI
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• v.68
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• pp.49-63
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• 2008

This paper describes the development and assessment of a hidden Markov model (HMM) based Tagalog speech synthesis system, where Tagalog is the most widely spoken indigenous language of the Philippines. Several aspects of the design process are discussed here. In order to build the synthesizer a speech database is recorded and phonetically segmented. The constructed speech corpus contains approximately 89 minutes of Tagalog speech organized in 596 spoken utterances. Furthermore, contextual information is determined. The quality of the synthesized speech is assessed by subjective tests employing 25 native Tagalog speakers as respondents. Experimental results show that the new system is able to obtain a 3.29 MOS which indicates that the developed system is able to produce highly intelligible neutral Tagalog speech with stable quality even when a small amount of speech data is used for HMM training.

• Speech Sciences
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• v.11 no.4
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• pp.129-141
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• 2004

An auditory-perceptual evaluation has long been utilized in assessing dysarthric speech. The process involves subjective judgement and the results might vary depending on clinical experiences or training of listeners. This study aimed to investigate reliability of the auditory-perceptual evaluation of 22 multi -dimensional variables on 6 patients with Parkinsonian speech disorders. Listeners were divided into two groups: one consisted of 6 speech therapists with clinical experiences for three years or more, and the other 6 graduate students without any previous clinical background. The results showed that the former evaluated dysarthric speech with higher inter-rater and intra-rater reliabilities than the latter. Furthermore, such speech variables as 'precise consonant: 'speech intelligibility: and 'SMR regularity' were more influenced than others by clinical experiences. We, therefore, postulated that a reliable auditory-perceptual evaluation of dysarthric speech may require adequate amount of clinical training of listeners.

• MALSORI
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• no.60
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• pp.145-164
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• 2006

This paper proposes class histogram equalization (CHEQ) to compensate noisy acoustic features for robust speech recognition. CHEQ aims to compensate for the acoustic mismatch between training and test speech recognition environments as well as to reduce the limitations of the conventional histogram equalization (HEQ). In contrast to HEQ, CHEQ adopts multiple class-specific distribution functions for training and test environments and equalizes the features by using their class-specific training and test distributions. According to the class-information extraction methods, CHEQ is further classified into two forms such as hard-CHEQ based on vector quantization and soft-CHEQ using the Gaussian mixture model. Experiments on the Aurora 2 database confirmed the effectiveness of CHEQ by producing a relative word error reduction of 61.17% over the baseline met-cepstral features and that of 19.62% over the conventional HEQ.