Name
Abstract | ||
|---|---|---|
Vowels exhibit high sonority and loudness due to varying strength of impulse-like excitations. Acoustic events such as vowel onset point (VOP) and vowel end point (VEP) can be used to detect precise vowel regions in a speech signal. In this paper, a technique is proposed to detect vowel regions based on these acoustic parameters in a continuous speech signal. Vowels possess significant energy content in the low frequency bands of speech. The initial phase of this method consists of speech signal processing using zero frequency filtering technique. Zero frequency filtered signal predominantly contains low frequency content of the speech signal as it is filtered around 0Hz. This process is followed by the extraction of dominant spectral peaks from the magnitude spectrum around glottal closure regions of the speech signal. The vowel onset points and vowel end points are obtained by convolving spectrum of zero frequency filtered signal with first order Gaussian differentiator. The performance of the proposed vowel region detection method is compared with the existing state of art methods on TIMIT database. It is reported that this method produced relatively significant improvement in vowel region detection in clean and noisy environments. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-58130-9_8 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Vowel Onset Point (VOP),Vowel End Point (VEP),Zero frequency filtering,Magnitude spectrum,First order Gaussian differentiator | Loudness,Signal processing,Mid vowel,Low frequency,Differentiator,Speech recognition,Gaussian,Vowel,Sonority hierarchy,Mathematics | Conference |
Volume | ISSN | Citations |
10089 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramakrishna Thirumuru | 1 | 0 | 1.35 |
| hari krishna vydana | 2 | 16 | 4.67 |
| Gangashetty, S.V. | 3 | 20 | 5.71 |
| Anil Kumar Vuppala | 4 | 27 | 5.71 |