Automatic Word Recognition for Bangla Spoken Language
We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervisor Dr. Mohammad Nurul Huda, Professor, United International University(UIU), Dhaka, Bangladesh, for his constant supervis...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Thesis |
| Sprog: | engelsk |
| Udgivet: |
Department of Computer Science and Engineering, Military Institute of Science and Technology
2015
|
| Fag: | |
| Online adgang: | http://hdl.handle.net/123456789/138 |
| Tags: |
Ingen Tags, Vær først til at tagge denne postø!
|
| _version_ | 1868227004607758336 |
|---|---|
| author | Zinnat, Sara Binte Hossain, Md. Imamul Asheque Siddique, Razia Marzia |
| author_browse | Asheque Siddique, Razia Marzia Hossain, Md. Imamul Zinnat, Sara Binte |
| author_facet | Zinnat, Sara Binte Hossain, Md. Imamul Asheque Siddique, Razia Marzia |
| author_sort | Zinnat, Sara Binte |
| collection | DSpace |
| description | We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervisor Dr. Mohammad Nurul Huda, Professor, United International University(UIU), Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis.
We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work.
Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis. |
| format | Thesis |
| id | oai:localhost:123456789-138 |
| institution | My University |
| language | English |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Computer Science and Engineering, Military Institute of Science and Technology |
| publisherStr | Department of Computer Science and Engineering, Military Institute of Science and Technology |
| record_format | dspace |
| spelling | oai:localhost:123456789-1382015-08-04T08:22:27Z Automatic Word Recognition for Bangla Spoken Language Zinnat, Sara Binte Hossain, Md. Imamul Asheque Siddique, Razia Marzia Automatic, Word, Recognition, Bangla Spoken, Language We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervisor Dr. Mohammad Nurul Huda, Professor, United International University(UIU), Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis. We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work. Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis. Automaticspeechrecognition(ASR)knownasspeechrecognitionisacomputertechnology that enables a device to recognize and understand spoken words, by digitizing the sound and matching its pattern against the stored patterns. In short, it is the conversion of spoken words to text. Currently available devices are largely speaker-dependent and can recognize discrete speech better than the normal (continuous) speech. In our research, we have used a system which is speaker independent (recognize speech of indefinite multiple people) and candetectcontinuousspeech. Theirmajorapplicationsareinassistiveforhelpingpeoplein working around their disabilities. Our proposed Bangla word system, based on LF-25 is a new approach towards the field of Bangla ASR system. For this thesis work, we have prepared a Bangla word recognition system of Bangla ASR. Most of the Bangla ASR system uses a small number of speakers, but 40 speakers selected from a wide area of Bangladesh, where Bangla is used as a native language, are involved here. In the experiments, Mel-Frequency Cepstral Coefficients (MFCCs)andLocalFeatures(LFs)areinputtedtotheHiddenMarkovModel(HMM)based classifiers for obtaining word recognition performance. Other than the traditional MFCC triphone model; a new method that have used LF based triphone model had been experimented to get better ASR performance. We used k-mean clustering for the proposed method. From the experimental results, word correct rate and word accuracy for male and female voices distinctly provide much better result for LF-25 than MFCC-38 as well as MFCC-39. So, our proposed system is in favor of gender independent fact. For male and female voices collectively, sometimes MFCC-39 based model and sometimes LF-25 based model shows better word accuracy and correct rate. Department of Computer Science and Engineering, Military Institute of Science and Technology 2015-07-01T08:29:04Z 2015-07-01T08:29:04Z 2013-12 Thesis http://hdl.handle.net/123456789/138 en B.Sc. in Computer Science and Engineering Thesis; application/pdf Department of Computer Science and Engineering, Military Institute of Science and Technology |
| spellingShingle | Automatic, Word, Recognition, Bangla Spoken, Language Zinnat, Sara Binte Hossain, Md. Imamul Asheque Siddique, Razia Marzia Automatic Word Recognition for Bangla Spoken Language |
| title | Automatic Word Recognition for Bangla Spoken Language |
| title_full | Automatic Word Recognition for Bangla Spoken Language |
| title_fullStr | Automatic Word Recognition for Bangla Spoken Language |
| title_full_unstemmed | Automatic Word Recognition for Bangla Spoken Language |
| title_short | Automatic Word Recognition for Bangla Spoken Language |
| title_sort | automatic word recognition for bangla spoken language |
| topic | Automatic, Word, Recognition, Bangla Spoken, Language |
| url | http://hdl.handle.net/123456789/138 |
| work_keys_str_mv | AT zinnatsarabinte automaticwordrecognitionforbanglaspokenlanguage AT hossainmdimamul automaticwordrecognitionforbanglaspokenlanguage AT ashequesiddiqueraziamarzia automaticwordrecognitionforbanglaspokenlanguage |