Automatic Isolated Arabic Speech Recognition and Its Transformation into Signs
In this technological era, providing a decent social integration of the mute communities or for the people with special needs still stands as a challenge. Currently, Sign Language (SL) is the main tool of communication between literate mute communities. About 18 million of the mute community is from...
Uloženo v:
| Vydáno v: | 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP) s. 148 - 152 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.07.2019
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | In this technological era, providing a decent social integration of the mute communities or for the people with special needs still stands as a challenge. Currently, Sign Language (SL) is the main tool of communication between literate mute communities. About 18 million of the mute community is from the Arabic world [1]. In this framework, this work focuses on the design and development of an effective approach for automatic isolated Arabic speech based message recognition. The objective is to achieve an effective solution with a high level of precision. It is realizable by smartly using the hybrid features extraction and the robust classification techniques. The incoming speech segment is enhanced by the application of appropriate pre-conditioning. The Mel-Frequency Cepstral Coefficients (MFCCs) and the Perceptive Linear Prediction Coding Coefficients (PLPCC) are extracted from the enhanced speech segment. Later specifically designed voting based robust classifier issued to compare these extracted features with the reference templates. The comparison outcomes are the basis of classification decisions. The classification decision is transformed into systematic visual signs. The system functionality is tested with the help of a prototype realization. An average subject dependent Arabic isolated speech recognition accuracy of 92.6% is achieved. |
|---|---|
| AbstractList | In this technological era, providing a decent social integration of the mute communities or for the people with special needs still stands as a challenge. Currently, Sign Language (SL) is the main tool of communication between literate mute communities. About 18 million of the mute community is from the Arabic world [1]. In this framework, this work focuses on the design and development of an effective approach for automatic isolated Arabic speech based message recognition. The objective is to achieve an effective solution with a high level of precision. It is realizable by smartly using the hybrid features extraction and the robust classification techniques. The incoming speech segment is enhanced by the application of appropriate pre-conditioning. The Mel-Frequency Cepstral Coefficients (MFCCs) and the Perceptive Linear Prediction Coding Coefficients (PLPCC) are extracted from the enhanced speech segment. Later specifically designed voting based robust classifier issued to compare these extracted features with the reference templates. The comparison outcomes are the basis of classification decisions. The classification decision is transformed into systematic visual signs. The system functionality is tested with the help of a prototype realization. An average subject dependent Arabic isolated speech recognition accuracy of 92.6% is achieved. |
| Author | Alhassani, Bashaier Alharbi, Ozuf Qaisar, Saeed Mian |
| Author_xml | – sequence: 1 givenname: Saeed Mian surname: Qaisar fullname: Qaisar, Saeed Mian email: sqaisar@effatuniversity.edu.sa organization: College of Engineering, Effat University, Jeddah, KSA – sequence: 2 givenname: Bashaier surname: Alhassani fullname: Alhassani, Bashaier email: bhalhassani@effat.edu.sa organization: College of Engineering, Effat University, Jeddah, KSA – sequence: 3 givenname: Ozuf surname: Alharbi fullname: Alharbi, Ozuf email: omalharbi@effat.edu.sa organization: College of Engineering, Effat University, Jeddah, KSA |
| BookMark | eNotj1FLwzAUhSPog5v-AkHyBzrvbdo0eSxlamE4WefzSNObGdiS0cYH_72T7elwPjgfnBm7DTEQY88IC0TQL137uVk3y65b5IB6oZRUspQ3bIZVrlBICXjPPuqfFI8mecvbKR5MooHXo-nPvTsR2W--IRv3wScfAzdh4G2a-HY0YXJx_B-esQ8p8s7vw_TA7pw5TPR4zTn7el1um_dstX5rm3qV-RxEynRJqIrB2rzoK2VzMA6cBmeoLB0VVQUCFVptAQuRD70B3QvUUIEsew2FmLOni9cT0e40-qMZf3fXi-IPewZMFA |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/SIPROCESS.2019.8868656 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Xplore POP ALL IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE/IET Electronic Library (IEL) (UW System Shared) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 1728136601 9781728136608 |
| EndPage | 152 |
| ExternalDocumentID | 8868656 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i203t-95e184dcc24b78c20af0f90fae55fe47703181c9c01432dba09b31907065b9043 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000557898200030&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Thu Jun 29 18:38:18 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i203t-95e184dcc24b78c20af0f90fae55fe47703181c9c01432dba09b31907065b9043 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_8868656 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-July |
| PublicationDateYYYYMMDD | 2019-07-01 |
| PublicationDate_xml | – month: 07 year: 2019 text: 2019-July |
| PublicationDecade | 2010 |
| PublicationTitle | 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP) |
| PublicationTitleAbbrev | SIPROCESS |
| PublicationYear | 2019 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.6990982 |
| Snippet | In this technological era, providing a decent social integration of the mute communities or for the people with special needs still stands as a challenge.... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 148 |
| SubjectTerms | arabic sign language arabic speech recognition Assistive technology Feature extraction features extraction Gesture recognition Linear predictive coding Mel frequency cepstral coefficient mel-frequency cepstral coefficients (MFCC) perceptual linear predictive coding coefficients (PLPCC) Speech recognition |
| Title | Automatic Isolated Arabic Speech Recognition and Its Transformation into Signs |
| URI | https://ieeexplore.ieee.org/document/8868656 |
| WOSCitedRecordID | wos000557898200030&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG6AePCkBozv9ODRle7S7eNIiEQSgwTQcCNtd6p76ZJl8ffbLoiaePHWNk3aTGc6XzsvhG4ZDWqbsUhqnkXUQ35_DzKIMhmbXpxqk9Q1ll6f-HgsFgs5aaC7fSwMANTOZ3AfmrUtPyvMJnyVdYVgwuOPJmpyzraxWrug35jI7mw0mT4P_LaDw1bggHryr6optdIYHv1vuWPU-Y6-w5O9XjlBDXBtNO5vqqJOr4pHnl08Qsxwv1Ta92crAPOOp1-uQIXDymV4VK3x_Acs9cO5qwo8y9_cuoNehg_zwWO0q4UQ5QnpVZFMwb_FMmMSqrkwCVGWWEmsgjS1QHlIQy9iI03I15dkWhGpvXSRYMXUktDeKWq5wsEZwuCRqpdKZQEsjYkS3EibWAqEKs6An6N2oMVytU13sdyR4eLv4Ut0GMi99WC9Qq2q3MA1OjAfVb4ub-oz-gQ515R1 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEJ4gmuhJDRjf9uDRle7SffRIiISNuBJAw410u1PdS5fA4u-3XRA18eKtbZq0mc50vnZeALcBs2o7CByehpnDDOQ392CATsZd2Xb9VHpVjaXXQZgk0XTKhzW428bCIGLlfIb3tlnZ8rNCruxXWSuKgsjgjx3Y9Rnz6DpaaxP261LeGsfD0XPXbNy6bFkeqKb_qptSqY3e4f8WPILmd_wdGW41yzHUUDcg6azKokqwSmLDMAYjZqSzEKnpj-eI8p2MvpyBCk2EzkhcLsnkBzA1w7kuCzLO3_SyCS-9h0m372yqITi5R9ulw300r7FMSo-lYSQ9KhRVnCqBvq-QhTYRfeRKLm3GPi9LBeWpkS9q7Zgpp6x9AnVdaDwFggarGrkUClExl4oolFx5iiFlIgwwPIOGpcVsvk54MduQ4fzv4RvY70-eBrNBnDxewIEl_dqf9RLq5WKFV7AnP8p8ubiuzusTII-XvA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2019+IEEE+4th+International+Conference+on+Signal+and+Image+Processing+%28ICSIP%29&rft.atitle=Automatic+Isolated+Arabic+Speech+Recognition+and+Its+Transformation+into+Signs&rft.au=Qaisar%2C+Saeed+Mian&rft.au=Alhassani%2C+Bashaier&rft.au=Alharbi%2C+Ozuf&rft.date=2019-07-01&rft.pub=IEEE&rft.spage=148&rft.epage=152&rft_id=info:doi/10.1109%2FSIPROCESS.2019.8868656&rft.externalDocID=8868656 |