{"created":"2020-09-01T14:29:33.118787+00:00","id":4305,"links":{},"metadata":{"_buckets":{"deposit":"48485275-2a28-46a1-a9fc-e57ae30171fa"},"_deposit":{"id":"4305","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4305"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4305","sets":["1582963302567:1597824322519"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"A Study on Isolated-Word Myanmar Speech Recognition via Artificial Neural Networks","subitem_1551255648112":"en_US"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Speech is an easiest way to communicate with each other. Digital processing of speechsignals is very important for speedy and precise automatic speech recognition systems.Speech recognition is the capability of an electronic device to understand spoken words,i.e. the process of decoding an acoustic speech signal captured by a microphone or amobile phone to a set of words. It is a technology that can be useful in many applicationsof our daily life, e.g. mobile communications, and has also become a challenge towardshuman-computer interfacing (HMI) technology.This thesis aims to develop an efficient speech recognition system for isolatedMyanmar words based on the theories of digital signal processing, speech processing, andartificial neural network techniques. The proposed system is intended to achieve speakerdependent recognition as well as speaker independent recognition.A speech signal is combined with voice and unvoiced sounds. In addition, eachword in the speech is typically surrounded with silence, which may be a hindrance forsuccessful speech recognition. So firstly in this system, the input speeches are manuallypreprocessed by using the Audacity software in order to detect the start and end points ofwords and remove unwanted parts like silences in speeches. This system then extracts theacoustically representative features like Mel-Frequency Cepstral Coefficients from thepreprocessed speech signals. Finally, those features are used to train a recognition modelof neural network with the Backpropagation algorithm for classification and recognitionof input speeches. Based on the knowledge learned during training, the recognition modelis expected to recognize the same speech by untrained new speakers (i.e. speakerindependent recognition).The proposed system in this thesis is developed to recognize twenty isolatedMyanmar words, which are the names of the cities in Rakhine state, Shan state, andKachin state in Myanmar. This system consists of a database which is made up oftraining and testing data sets with 2400 and 400 utterances respectively. The trainingwords are uttered by 10 speakers (4 males and 6 females) who are university graduatestudents. As for speaker independent recognition, testing utterances are the same wordsas in training but uttered by different speakers than the ones participated in training. Theivproposed system is implemented in MATLAB and experimental results show that itachieved the recognition rate of about 93.5% for known speakers (i.e. speaker dependent)and 76.5% for unknown speakers (i.e. speaker independent)."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-09-23"}],"displaytype":"preview","filename":"Nan Phyu Phyu Hsan(5CT-1)_Thesis.pdf","filesize":[{"value":"1614 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4305/files/Nan Phyu Phyu Hsan(5CT-1)_Thesis.pdf"},"version_id":"209ebb00-9c04-4772-bc44-882ddf18939b"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"University of Computer Studies, Yangon","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Hsan, Nan Phyu Phyu"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Thesis"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2018-11"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/2245"},"item_title":"A Study on Isolated-Word Myanmar Speech Recognition via Artificial Neural Networks","item_type_id":"21","owner":"1","path":["1597824322519"],"publish_date":"2019-09-23","publish_status":"0","recid":"4305","relation_version_is_last":true,"title":["A Study on Isolated-Word Myanmar Speech Recognition via Artificial Neural Networks"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T01:39:39.345302+00:00"}