• MALSORI
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• no.47
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• pp.97-107
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• 2003

Speaker change detection is to detect automatically a point of time at which speaker was replaced. Since feature parameters used for speaker change detection depend not only on speaker characteristics but also on phonetic characteristics, spoken contents included in the feature parameters inevitably causes performance degradation of speaker change detection. In this paper, to alleviate this problem, a method to normalize phonetic variations in speech feature parameters is proposed for emphasizing changes due to speaker characteristics. Experimental results show that the proposed method improves the performance of speaker change detection.

• Speech Sciences
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• v.10 no.3
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• pp.213-224
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• 2003

Spoken sound includes not only speaker's source but the characteristics of vocal tract and speech radiation. This paper is based on the theory of Park[1], who proposes the Phonation Type Index k; a variable that shows the characteristic of speaker's source excluding those of speaker's vocal tract and speech radiation. With Park's theory, we collect data by changing recording environments and expanding experimental data, and analyze the data collected to see whether or not the PTI k shows good discriminating power as a variable for speaker recognition. In the experiment, we repeatedly record 8 sentences ten times for each of 5 males in the environment of a recording room and an office, extract PTI k for each speaker, and measure the discriminating power for each speaker by using the value of PTI k. The result shows that PTI k has the excellent discriminating power of speakers. We also confirm that, even if the recording environment is changed, PTI k shows similar results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.763-766
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• 2004

Recently, various acoustic artifacts that contains speaker have been produced such as cellular phone. Speaker consists of diaphragm generating sound and coil vibrating diaphragm. Generally, good speaker means that it has a wide frequency range, high output power rate to input power and flat sound pressure level in specified frequency range. Acoustic characteristic was estimated through the experiment and computer simulation, or sound power was controlled with acoustic sensitivity in a natural frequency range fer last decade. However, the flatness of sound pressure level has not been considered to enhance the sound quality of a speaker. Tn this study, a method for speaker design is proposed for a good acoustic characteristic, which is flatness of SPL(sound pressure level) and wideness between the first and second natural frequency. SYSNOISE is used fer acoustic analysis and ANSYS is used for harmonic response analysis and modal analysis. Optimization for acoustic characteristics of a speaker diaphragm is performed using ModelCenter. All analyses are done within a frequency domain. And we confirm that the experimental and computational simulations have similar trend.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.69-77
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• 2002

Speaker verification can be classified in two categories, text-dependent speaker verification and text-independent speaker verification. In this paper, we discuss text-dependent speaker verification. Text-dependent speaker verification system determines whether the sound characteristics of the speaker are equal to those of the specific person or not. In this paper we obtain the speaker data using a sound card in various noisy conditions, apply a new Hidden LMS (Least Mean Square) adaptive algorithm to it, and extract LPC (Linear Predictive Coding)-cepstrum coefficients as feature vectors. Finally, we use a competitive learning neural network for speaker verification. The proposed hidden LMS adaptive filter using a neural network reduces noise and enhances features in various noisy conditions. We construct a separate neural network for each speaker, which makes it unnecessary to train the whole network for a new added speaker and makes the system expansion easy. We experimentally prove that the proposed method improves the speaker verification performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.6993-6997
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• 2014

The aim of this study was to experimentally investigate the sound quality characteristics, such as sound deflection, sound pressure level and frequency characteristics of a magnetic type speaker in an anechoic chamber to overcome the sound quality and voice-coil temperature problems. To accomplish this, the sound quality performance of the magnetic type speaker was tested according to the magnetic fluid amount and magnetic field intensity. The sound deflection, sound pressure level, and frequency characteristics were measured using the Smarrt program. As a result, at a magnetic fluid amount of 2.4 ml, the sound deflection and the sound pressure level of the magnetic type speaker were enhanced by comparing with those of the general type speaker. The frequency characteristics and the sound pressure level of the magnetic type speaker were enhanced greatly with increasing magnetic field intensity from 8.06 mT to 9.10 mT. In addition, the sound deflection of the magnetic type speaker was 0.01% lower than that of the general type speaker.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.1
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• pp.5-12
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• 2016

This paper describes the development process for vibration and acoustic characteristics of a balanced armature speaker. The design parameters were chosen in consideration of the influence of the bending stiffness of balanced armature which is the form of a cantilever structure in the speaker. For study of the performance of the speaker according to the design parameters, in the first step, we analyzed the characteristics of the velocity of the diaphragm to the electrical input. Next step, acoustic characteristics were analyzed by structural-acoustic coupled analysis. And the reliability of the analysis was verified by comparing the result of analysis with test results. Finally, we proposed a design method for implementing an enhanced balanced armature speakers through analysis method.

• MALSORI
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• no.45
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• pp.93-105
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• 2003

In this paper, we present a single framework based on GMM for speaker recognition. The proposed framework can simultaneously minimize environmental variations on mismatched conditions and adapt the bias free and speaker-dependent characteristics of claimant utterances to the background GMM to create a speaker model. We compare the closed-set speaker identification for conventional method and the proposed method both on TIMIT and NTIMIT. In the several sets of experiments we show the improved recognition rates on a simulated channel and a telephone channel condition by 7.2% and 27.4% respectively.

• 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.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.30 no.1
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• pp.25-32
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• 1994

An underwater speaker was made of a moving coil driver unite of usual speaker, acryl-boards, polyester resin, rubber and castor oil and it's frequency characteristics was measured in range of 250~600Hz in air water tank and sea. The results of measurements are follows: 1. Transmitting and receiving frequency of measurement frequency were similar in air, water tank and sea. 2. The input and output wave forms of a manufactured speaker which is not water-proof in air were similar to each other in 300~450Hz, but other frequencies showed distorted wave forms. 3. The input and output wave forms of an underwater speaker in water thank and sea were similar to each other in 250~600Hz. But output wave forms showed combination waves with very low frequency. 4. Transmitting and receiving frequency wave forms and resisting pressure of an underwater speaker at 80m in the depth of water were in good condition. Therefore it can be possible to use it as an underwater speaker.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.739-743
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• 2006

In this paper, development of voice activated Universal Remote Control using the Neural Networks. A speaker dependent system is developed to operate for a single speaker. These systems are usually easier to develop, cheaper to buy and more accurate, but not as flexible as speaker adaptive or speaker independent systems. A speaker independent system is developed to operate for any speaker of a particular type (e.g. American English). These systems are the most difficult to develop, most expensive and accuracy is lower than speaker dependent systems. However, they are more flexible. A speaker adaptive system is developed to adapt its operation to the characteristics of new speakers. It's difficulty lies somewhere between speaker independent and speaker dependent systems. This paper is developed Speaker Adaptation using the Neural Networks.