• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.109-117
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• 2021

Recently, the use of speech-based interfaces is increasing as a means for human-computer interaction (HCI). Accordingly, interest in post-processors for correcting errors in speech recognition results is also increasing. However, a lot of human-labor is required for data construction. in order to manufacture a sequence to sequence (S2S) based speech recognition post-processor. To this end, to alleviate the limitations of the existing construction methodology, a new data construction method called Back TranScription (BTS) was proposed. BTS refers to a technology that combines TTS and STT technology to create a pseudo parallel corpus. This methodology eliminates the role of a phonetic transcriptor and can automatically generate vast amounts of training data, saving the cost. This paper verified through experiments that data should be constructed in consideration of text style and domain rather than constructing data without any criteria by extending the existing BTS research.

• MALSORI
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• no.43
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• pp.57-72
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• 2002

The technology of speech recognition has a wide field of application. The range of such technology is spreading into mobile computing having the large amount of movement for communication equipments at the present time. Particularly, recognition in internet environment is rapidly moving into mobile environment. Because of these environments, users want the faster speed of data transmission and the lighter portable equipment for data access. That is PDA(Personal Digital Assistant). Therefore, we designed a triphone-based text independent vocabulary recognizer for the implementation of speech control in this paper. The text independent vocabulary recognizer is based on the state .joint algorithm with decision trees

• MALSORI
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• no.43
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• pp.127-136
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• 2002

The speaker adaptation technique is generally used to reduce the speaker difference in speech recognition. In this work, we focus on the features fitted to a linear regression-based speaker adaptation. These are obtained by feature transformation based on independent component analysis (ICA), and the transformation matrix is learned from a speaker independent training data. When the amount of data is small, however, it is necessary to adjust the ICA-based transformation matrix estimated from a new speaker utterance. To cope with this problem, we propose a smoothing method: through a linear interpolation between the speaker-independent (SI) feature transformation matrix and the speaker-dependent (SD) feature transformation matrix. We observed that the proposed technique is effective to adaptation performance.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.119-122
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• 2002

This paper focuses on building up a database of commercial stocks using XML syntax and looks into a way of building up a system with the combination of XML and XSLT that provides connectivity to client-server databases through vocal means. The use of XSLT has several advantages. Most importantly, it can transform a type of data into different formats. A vocal interface minimizes some space and time limits imposed on users outside premises when they need an instant connection to their database. In this fashion, the users can check information on stock lists without being pressurized by certain limits. PC, PDAs and cellular phones are some examples of mobile connection. The use of VoiceXML creates vocal applications. In VoiceXML servies, users can gain immediate access to data upon the input of their voices and the DTMF signals of the telephone.

• ETRI Journal
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• v.32 no.5
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• pp.810-818
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• 2010

This paper presents a new framework for integrating untranscribed spoken content into the acoustic training of an automatic speech recognition system. Untranscribed spoken content plays a very important role for under-resourced languages because the production of manually transcribed speech databases still represents a very expensive and time-consuming task. We proposed two new methods as part of the training framework. The first method focuses on combining initial acoustic models using a data-driven metric. The second method proposes an improved acoustic training procedure based on unsupervised transcriptions, in which word endings were modified by broad phonetic classes. The training framework was applied to baseline acoustic models using untranscribed spoken content from parliamentary debates. We include three types of acoustic models in the evaluation: baseline, reference content, and framework content models. The best overall result of 18.02% word error rate was achieved with the third type. This result demonstrates statistically significant improvement over the baseline and reference acoustic models.

• MALSORI
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• no.49
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• pp.135-144
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• 2004

In this paper, we make a study of classification normal from abnormal - normal, asthma through analysis of thoracic sound to take use thoracic sound detection system. Thoracic sound detection system has a function to store thoracic sound and analyze the data. The wave shape of thoracic sound is similar to noise and is systematically generated by inhalation and exhalation breathing, therefore, in this paper, to classify asthma sound in thoracic sound, we could discriminate between normal and abnormal case using level crossing rate(LCR) and spectrogram energy rate.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.141-143
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• 2003

Speech recognition performance depends on various factors. One of the factors is the characteristic and established distance of a microphone which is used when speech data is collected. Thus, in the present experiment speech databases for tests are created through the type and established distance of a microphone. Then, acoustic models are built based on these databases, and each of the acoustic models is assessed by the data to determine recognition performance depending on various microphones and established microphone distances.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.69-72
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• 2003

In this paper, we investigate various factors that are relevant to design and implementation of an integrated management system for various speech corpora. The purpose of this paper is to manage an integrated management system for various kinds of speech corpora necessary for speech research and speech corpora consrtructed in different data formats. In addition, ways are considered to allow users to search with effect for speech corpora that meet various conditions which they want, and to allow them to add with ease corpora that are constructed newly. In order to achieve this goal, we design a global schema for an integrated management of new additional information without changing old speech corpora, and construct a web-based integrated management system based on the scheme that can be accessed without any temporal and spatial restrictions. And we show the steps by which these can be implemented, and describe related future study topics, examining the system.

• MALSORI
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• no.53
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• pp.93-102
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• 2005

The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis. According to experimental results, the proposed temporal filtering method has shown slightly better performance than the previous ones.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.91-94
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• 2007

This paper aims to analyze the pronunciation of Korean Point-of-Interest (POI) data, which consist of 224 sound files, from the phonological point of view, adapting the notion of prosodic word within the framework of Intonational Phonology. Each POI word is broken down into prosodic words, which are defined as the minimal sequence of segments which can be produced as one Accentual Phrase (AP). Then the pronunciation of the POI word considering its prosodic words are analyzed. The results show that: in most cases, a prosodic word is realized as one AP; that, in some cases, two prosodic words are pronounced as one AP: and that no cases are found where 3 prosodic words are realized as one AP.