• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.297-298
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• 2023

COVID-19 가 사실상 종식됨에 따라 대학 강의가 비대면 온라인 강의에서 대면 강의로 전환되었다. 온라인 강의에서는 다시 보기를 통한 복습이 가능했지만, 대면강의에서는 녹음을 통해서 이를 대체하고 있다. 하지만 다시 보기와 녹음본은 원하는 부분을 찾거나 내용을 요약하는데 있어서 시간이 오래 걸리고 불편하다. 본 논문에서는 강의 내용을 STT(Speech-to-Text) 기술을 활용하여 텍스트로 변환하고 ChatGPT(Chat-Generative Pre-trained Transformer)로 요약하는 애플리케이션을 제안한다.

• Phonetics and Speech Sciences
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• v.5 no.4
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• pp.217-225
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• 2013

This paper describes the design and implementation of the kWebAnywhere system based on WebAnywhere, which assists people with severely diminished eye sight and the blind people to access Internet information through Web interfaces. The WebAnywhere is a server-based web reader which reads aloud the web contents using TTS(text-to-speech) technology on the Internet without installing any software on the client's system. The system can be used in general web browsers using a built-in audio function, for blind users who are unable to afford to use a screen reader and for web developers to design web accessibility. However, the WebAnywhere is limited to supporting only a single language and cannot be applied to Korean web contents directly. Thus, in this paper, we modified the WebAnywhere to serve multiple language contents written in both English and Korean texts. The modified WebAnywhere system is called kWebAnywhere to differentiate it with the original system. The kWebAnywhere system is modified to support the Korean TTS system, VoiceText$^{TM}$, and to include user interface to control the parameters of the TTS system. Because the VoiceText$^{TM}$ system does not support the Festival API used in the WebAnywhere, we developed the Festival Wrapper to transform the VoiceText$^{TM}$'s private APIs to the Festival APIs in order to communicate with the WebAnywhere engine. We expect that the developed system can help people with severely diminished eye sight and the blind people to access the internet contents easily.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.285-292
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• 2002

One of the problems that should be solved in Text-To-Speech (TTS) is discontinuities at unit-joining points. To cope with this problem, a smoothing method using a low-pass filter is employed in this paper, In the proposed soothing method, a filter coefficient that controls the amount of smoothing is determined according to contort information to be synthesized. This method efficiently reduces both discontinuities at unit-joining points and artifacts caused by undesired smoothing. The amount of smoothing is determined with discontinuities around unit-joins points in the current synthesized speech and discontinuities predicted from context. The discontinuity predictor is implemented by CART that has context feature variables. To evaluate the performance of the proposed method, a corpus-based concatenative TTS was used as a baseline system. More than 6075 of listeners realized that the quality of the synthesized speech through the proposed smoothing is superior to that of non-smoothing synthesized speech in both naturalness and intelligibility.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2649-2652
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• 2003

In this Paper, an Audio-Visual Teaching aid (AVTA) for use in a classroom and with Internet is presented. A system, which was designed and tested, consists of a wireless Microphone system, Text to Speech conversion Software, Noise filtering circuit and a Computer. An IBM compatible PC with sound card and Network Interface card and a Web browser and a voice and text messenger service were used to provide slightly delayed text and also voice over the internet for remote teaming, while providing scrolling text from a real time lecture in a classroom. The motivation for design of this system, was to aid Korean students who may have difficulty in listening comprehension while have, fairly good reading ability of text. This application of this system is twofold. On one hand it will help the students in a class to view and listen to a lecture, and on the other hand, it will serve as a vehicle for remote access (audio and text) for a classroom lecture. The project provides a simple and low cost solution to remote learning and also allows a student to have access to classroom in emergency situations when the student, can not attend a class. In addition, such system allows the student in capturing a teacher's lecture in audio and text form, without the need to be present in class or having to take many notes. This system will therefore help students in many ways.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• MALSORI
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• no.56
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• pp.207-223
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• 2005

The goal of language model adaptation is to improve the background language model with a relatively small adaptation corpus. This study presents a language model adaptation technique where additional text data for the adaptation do not exist. We propose the information retrieval (IR) technique with N-gram language modeling to collect the adaptation corpus from baseline text data. We also propose to use a dynamic language model interpolation coefficient to combine the background language model and the adapted language model. The interpolation coefficient is estimated from the word hypotheses obtained by segmenting the input speech data reserved for held-out validation data. This allows the final adapted model to improve the performance of the background model consistently The proposed approach reduces the word error rate by $13.6\%$ relative to baseline 4-gram for two-hour broadcast news speech recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.89-92
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• 2016

The latest the siri and like this is offering services that recognize and respond to words in the smartphone or web services. In order to handle intelligently these voices, It needs to search big data in the cloud and requires the implementation of parsing context accuracy given. In this paper, I would like to propose the study on the intelligent personal assistant development method base on the Open source with ASR(Automatic Speech Recognition), QAS(Question Answering System) and TTS(Text To Speech).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1443-1453
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• 1998

This paper presents the speech synthesis engine that converts the character strings kept in a computer memory into the synthesized speech sounds with enhancing the intelligibility and the naturalness by adapting the waveform processing method. The speech engine using demisyllable speech segments receives command streams for pitch modification, duration and energy control. The command based engine isolates the high level processing of text normalization, letter-to-sound and the lexical analysis and the low level processing of signal filtering and pitch processing. The TTS(Text-to-Speech) system implemented by using the speech synthesis engine has three independent object modules of the Text-Normalizer, the Commander and the said Speech Synthesis Engine those of which are easily replaced by other compatible modules. The architecture separating the high level and the low level processing has the advantage of the expandibility and the portability because of the mix-and-match nature.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.359-366
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• 2022

In this paper, we present the Korean menu-ordering Sentence Text-to-Speech (TTS) system using conformer-based FastSpeech2. Conformer is the convolution-augmented transformer, which was originally proposed in Speech Recognition. Combining two different structures, the Conformer extracts better local and global features. It comprises two half Feed Forward module at the front and the end, sandwiching the Multi-Head Self-Attention module and Convolution module. We introduce the Conformer in Korean TTS, as we know it works well in Korean Speech Recognition. For comparison between transformer-based TTS model and Conformer-based one, we train FastSpeech2 and Conformer-based FastSpeech2. We collected a phoneme-balanced data set and used this for training our models. This corpus comprises not only general conversation, but also menu-ordering conversation consisting mainly of loanwords. This data set is the solution to the current Korean TTS model's degradation in loanwords. As a result of generating a synthesized sound using ParallelWave Gan, the Conformer-based FastSpeech2 achieved superior performance of MOS 4.04. We confirm that the model performance improved when the same structure was changed from transformer to Conformer in the Korean TTS.

• MALSORI
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• no.43
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• pp.73-88
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• 2002

In this paper, for natural facial synthesis, lip-synch algorithm based on key-frame method using RBF(radial bases function) is presented. For lips synthesizing, we make viseme range parameters from phoneme and its duration information that come out from the text-to-speech(TTS) system. And we extract viseme information from Av DB that coincides in each phoneme. We apply dominance function to reflect coarticulation phenomenon, and apply bilinear interpolation to reduce calculation time. At the next time lip-synch is performed by playing the synthesized images obtained by interpolation between each phonemes and the speech sound of TTS.