• The Journal of the Acoustical Society of Korea
• /
• v.22 no.4E
• /
• pp.150-154
• /
• 2003

The distortion effects of microphones have been analyzed and compensated at mel-frequency feature domain. Unlike popular bias removal algorithms a linear transformation of mel-frequency spectrum is incorporated. Although a diagonal matrix transformation is sufficient for medium-quality microphones, a full-matrix transform is required for low-quality microphones with severe nonlinearity. Proposed compensation algorithms are tested with HTIMIT database, which resulted in about 5 percents improvements in recognition rate over conventional CMS algorithm.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.20 no.2
• /
• pp.207-213
• /
• 2011

In this paper, we present a study on the real-time implementation of mobile robot to which the interactive voice recognition technique is applied. The speech command utters the sentential connected word and asserted through the wireless remote control system. We implement an automatic distance speech command recognition system for voice-enabled services interactively. We construct a baseline automatic speech command recognition system, where acoustic models are trained from speech utterances spoken by a microphone. In order to improve the performance of the baseline automatic speech recognition system, the acoustic models are adapted to adjust the spectral characteristics of speech according to different microphones and the environmental mismatches between cross talking and distance speech. We illustrate the performance of the developed speech recognition system by experiments. As a result, it is illustrated that the average rates of proposed speech recognition system shows about 95% above.

• Speech Sciences
• /
• v.7 no.3
• /
• pp.185-195
• /
• 2000

This paper seeks to compare the feature parameters used in speaker identification systems under noisy environments. The feature parameters compared are LP cepstrum (LPCC), Cepstral mean subtraction(CMS), Pole-filtered CMS(PFCMS), Adaptive component weighted cepstrum(ACW) and Postfilter cepstrum(PF). The GMM-based text independent speaker identification system is designed for this target. Some series of experiments show that the LPCC parameter is adequate for modelling the speaker in the matched environments between train and test stages. But in the mismatched training and testing conditions, modified parameters are preferable the LPCC. Especially CMS and PFCMS parameters are more effective for the microphone mismatching conditions while the ACW and PF parameters are good for more noisy mismatches.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.303-304
• /
• 2007

In this paper, we implement an automatic distance speech recognition system for voiced-enabled services. We first construct a baseline automatic speech recognition (ASR) system, where acoustic models are trained from speech utterances spoken by using a cross-talking microphone. In order to improve the performance of the baseline ASR using distance speech, the acoustic models are adapted to adjust the spectral characteristics of speech according to different microphones and the environmental mismatches between cross-talking and distance speech. Next we develop a voice activity detection algorithm for distance speech. We compare the performance of the base-line system and the developed ASR system on a task of PBW (Phonetically Balanced Word) 452. As a result it is shown that the developed ASR system provides the average word error rate (WER) reduction of 30.6 % compared to the baseline ASR system.