Content deleted Content added
m Sabemalek moved page Persian Consonant Vowel Combination Speech Dataset to PCVC Speech Dataset: PCVC is more famous |
mNo edit summary |
||
Line 1:
The '''PCVC (Persian Consonant Vowel Combination) Speech Dataset''' is a [[Modern Persian]] [[speech corpus]] for [[speech recognition]] and also [[speaker recognition]]. The dataset contains sound samples of [[Modern Persian]] combination of [[vowel]] and [[consonant]] phonemes from different speakers. Every sound sample contains just one consonant and one vowel So it is somehow labeled in phoneme level. This dataset contains of 23 Persian consonants and 6 vowels. The sound samples are all possible combinations of vowels and consonants (138 samples for each speaker). The sample rate of all speech samples is 48000 which means there are 48000 sound samples in every 1 second. Every sound sample starts with consonant then continues with vowel. In each sample, in average, 0.5 second of each sample is speech and the rest is silence. Each sound sample ends with silence.<ref> Malekzadeh, S., Gholizadeh, M.H. and Razavi, S.N., 2018. {{cite paper |title=Persian phonemes recognition using PPNet|url=https://arxiv.org/abs/1812.08600 }} arXiv preprint arXiv:1812.08600. </ref> All of sound samples are denoised with "Adaptive noise reduction" algorithm.<ref>{{cite paper |title=PCVC Kaggle page |url=https://www.kaggle.com/sabermalek/pcvcspeech/home }}</ref>
Compared to Farsdat speech dataset<ref>Bijankhan, M., Sheikhzadegan, J., Roohani, M. R., Samareh, Y., Lucas, C., & Tebyani, M. (1994). FARSDAT-The Speech Database of Farsi Spoken Language. The Proceedings of the Australian Conference on Speech Science and Technology (Vol. 2, pp. 826–831).</ref> and Persian speech corpus<ref>Halabi, Nawar (2016). Modern Standard Persian Phonetics for Speech Synthesis. University of Southampton, School of Electronics and Computer Science.</ref> it is more easy to use because it is prepared in .mat data files.<ref>{{cite paper |title= Access and change variables directly in MAT-files, without loading into memory. |url=https://uk.mathworks.com/help/matlab/ref/matfile.html }}</ref> Also it is more based on phoneme based separation and all samples are denoised.
| |||