• MALSORI
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• no.54
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• pp.1-14
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• 2005

This paper presents durational characteristics of Korean distant-talking speech using speech data, which consist of 500 distant-talking utterances and 500 normal utterances of 10 speakers (5 males and 5 females). Each file was segmented and labeled manually and the duration of each segment and each word was extracted. Using a statistical method, the durational change of distant-talking speech in comparison with normal speech was analyzed. The results show that the duration of words with distant-talking speech is increased in comparison with normal style, and that the average unvoiced consonantal duration is reduced while the average vocalic duration is increased. Female speakers show a stronger tendency towards lengthening the duration in distant-talking speech. Finally, this study also shows that the speakers of distant-talking speech could be classified according to their different duration rate.

• The Journal of the Acoustical Society of Korea
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• v.24 no.2E
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• pp.71-76
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• 2005

Compared to normal speech, distant-talking speech is characterized by the acoustic effect due to interfering sound and echoes as well as articulatory changes resulting from the speaker's effort to be more intelligible. In this paper, the acoustic features for distant-talking speech due to the articulatory changes will be analyzed and compared with those of the Lombard effect. In order to examine the effect of different distances and articulatory changes, speech recognition experiments were conducted for normal speech as well as distant-talking speech at different distances using HTK. The speech data used in this study consist of 4500 distant-talking utterances and 4500 normal utterances of 90 speakers (56 males and 34 females). Acoustic features selected for the analysis were duration, formants (F1 and F2), fundamental frequency, total energy and energy distribution. The results show that the acoustic-phonetic features for distant-talking speech correspond mostly to those of Lombard speech, in that the main resulting acoustic changes between normal and distant-talking speech are the increase in vowel duration, the shift in first and second formant, the increase in fundamental frequency, the increase in total energy and the shift in energy from low frequency band to middle or high bands.

• MALSORI
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• v.55
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• pp.61-76
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• 2005

This paper aims to analyze the acoustic effects of vowels produced in a distant-talking environment. The analysis was performed using a statistical method. The influence of gender and speakers on the variation was also examined. The speech data used in this study consist of 500 distant-talking words and 500 normal words of 10 speakers (5 males and 5 females). Acoustic features selected for the analysis were the duration, the formants (Fl and F2), the fundamental frequency and the total energy. The results showed that the duration, F0, F1 and the total energy increased in the distant-talking speech compared to normal speech; female speakers showed higher increase in all features except for the total energy and the fundamental frequency. In addition, speaker differences were observed.

• MALSORI
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• no.53
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• pp.119-127
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• 2005

Speech recognition is one of the user interface technologies in commanding and controlling any terminal such as a TV, PC, cellular phone etc. in a ubiquitous environment. In controlling a terminal, the mismatch between training and testing causes rapid performance degradation. That is, the mismatch decreases not only the performance of the recognition system but also the reliability of that. Therefore, the performance degradation due to the mismatch caused by the change of the environment should be necessarily compensated. Whenever the environment changes, environment adaptation is performed using the user's speech and the background noise of the changed environment and the performance is increased by employing the models appropriately transformed to the changed environment. So far, the research on the environment compensation has been done actively. However, the compensation method for the effect of distant-talking speech has not been developed yet. Thus, in this paper we apply MLLR-based environment adaptation to compensate for the effect of distant-talking speech and the performance is improved.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.87-90
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• 2005

The aim of this paper is to investigate the prosodic characteristics of Korean distant speech. 36 2-syllable words of 4 speakers (2 males and 2 females) produced in both distant-talking and normal environments were used. The results showed that ratios of second syllable to first syllable in vowel duration and vowel energy were significantly larger in the distant-talking environment compared to the normal environment and f0 range also bigger in the distant-talking environment. In addition, 'HL%' contour boundary tone in the second syllable and/or 'L +H' contour tone in the first syllable were used in the distant-talking environment.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.137-143
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• 2006

The aim of this paper is to investigate the prosodic characteristics of Korean distant speech. Four speakers (2 males and 2 females) produced 36 2-syllable words in both distant-talking and normal environments. totaling 288 spoken 2-syllable words. The results showed that ratios of second syllable to first syllable in vowel duration and vowel energy were significantly larger in the distant-talking environment compared to the normal environment and f0 range also bigger in the distant-talking environment. In addition, 'HL%' contour boundary tone in the second syllable and/or 'L+H' contour tone in the first syllable were used in the distant-talking environment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.215-220
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• 2005

Nowadays, various speech processing systems are being introduced in the fields of robotics. However, real-time processing and high performances are required to properly implement speech processing system for the autonomous robots. Achieving these goals requires advanced hardware techniques including intelligent software algorithms. For example, we need nonlinear amplifier boards which are able to adjust the compression radio (CR) via computer programming. And the necessity for noise reduction, double-buffering on EPLD (Erasable programmable logic device), simultaneous multi-channel AD conversion, distant sound localization will be explained in this paper. These ideas can be used to improve distant and omni-directional speech recognition. This speech processing system, based on embedded Linux system, is supposed to be mounted on the new home service robot, which is being developed at KIST (Korea Institute of Science and Technology)

• ETRI Journal
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• v.34 no.4
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• pp.583-590
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• 2012

In this paper, we present a new approach for speaker diarization. First, we use the prosodic information calculated on the original speech to resynthesize the new speech data utilizing the spectrum modeling technique. The resynthesized data is modeled with sinusoids based on pitch, vibration amplitude, and phase bias. Then, we use the resynthesized speech data to extract cepstral features and integrate them with the cepstral features from original speech for speaker diarization. At last, we show how the two streams of cepstral features can be combined to improve the robustness of speaker diarization. Experiments carried out on the standardized datasets (the US National Institute of Standards and Technology Rich Transcription 04-S multiple distant microphone conditions) show a significant improvement in diarization error rate compared to the system based on only the feature stream from original speech.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.33-38
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• 2018

Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.39-40
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• 2007

For efficient interaction between human and robots, speech interface is a core problem especially in noisy and reverberant conditions. This paper analyzes main issues of spoken language interface for humanoid robots, such as sound source localization, voice activity detection, and speaker recognition.