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This paper presents a new feature set for noisy speech recognition in autocorrelation domain. The autocorrelation domain is well-known for its pole preserving and noise separation properties. Therefore, in this paper we use the autocorrelation domain as an appropriate candidate for robust feature extraction. In our approach, initially, the lower lags of the(More)
In this paper, we present a mean quantization based audio watermarking scheme in the wavelet transform domain. The watermark data was embedded by quantizing the means of two selected bands of the wavelet transform of the original audio signal. One of the bands was in the lower frequency and the other one in the higher frequency ranges. Adaptive step sizes(More)
In this paper, we present several fusion approaches to merge speed limits reported in digital maps with detected speed limit signs using an onboard camera. Digital maps holding speed limits signs are required to be updated to cover speed limit changes and are unable to support variable speed limits. On the other hand, a camera system placed onboard a(More)
In this paper, our main purpose is to embed data in the frequency domain of audio signals. Data was embedded by means of quantization index modulation (QIM) in the frequency domain. With this aim, the spectrum of the audio signal was divided into two parts. The first part consisted of the first 19 Barks and the second included the remaining 6 Barks. Each of(More)
This paper shows research performed into the topic of speaker diarization for multi-speaker environment. It looks into the algorithms and the implementation of an offline speaker segmentation and indexing system for recorded speech data where usually more than one speaker is present. Speaker diarization is a well studied topic in the domain of broadcast(More)
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