{"title":"针对视力和听力障碍人士的摩斯密码语音识别技术","authors":"Ritabrata Roy Choudhury","doi":"arxiv-2407.14525","DOIUrl":null,"url":null,"abstract":"The proposed model aims to develop a speech recognition technology for\nhearing, speech, or cognitively disabled people. All the available technology\nin the field of speech recognition doesn't come with an interface for\ncommunication for people with hearing, speech, or cognitive disabilities. The\nproposed model proposes the speech from the user, is transmitted to the speech\nrecognition layer where it is converted into text and then that text is then\ntransmitted to the morse code conversion layer where the morse code of the\ncorresponding speech is given as the output. The accuracy of the model is\ncompletely dependent on speech recognition, as the morse code conversion is a\nprocess. The model is tested with recorded audio files with different\nparameters. The proposed model's WER and accuracy are both determined to be\n10.18% and 89.82%, respectively.","PeriodicalId":501178,"journal":{"name":"arXiv - CS - Sound","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Morse Code-Enabled Speech Recognition for Individuals with Visual and Hearing Impairments\",\"authors\":\"Ritabrata Roy Choudhury\",\"doi\":\"arxiv-2407.14525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed model aims to develop a speech recognition technology for\\nhearing, speech, or cognitively disabled people. All the available technology\\nin the field of speech recognition doesn't come with an interface for\\ncommunication for people with hearing, speech, or cognitive disabilities. The\\nproposed model proposes the speech from the user, is transmitted to the speech\\nrecognition layer where it is converted into text and then that text is then\\ntransmitted to the morse code conversion layer where the morse code of the\\ncorresponding speech is given as the output. The accuracy of the model is\\ncompletely dependent on speech recognition, as the morse code conversion is a\\nprocess. The model is tested with recorded audio files with different\\nparameters. The proposed model's WER and accuracy are both determined to be\\n10.18% and 89.82%, respectively.\",\"PeriodicalId\":501178,\"journal\":{\"name\":\"arXiv - CS - Sound\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Sound\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.14525\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Sound","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.14525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Morse Code-Enabled Speech Recognition for Individuals with Visual and Hearing Impairments
The proposed model aims to develop a speech recognition technology for
hearing, speech, or cognitively disabled people. All the available technology
in the field of speech recognition doesn't come with an interface for
communication for people with hearing, speech, or cognitive disabilities. The
proposed model proposes the speech from the user, is transmitted to the speech
recognition layer where it is converted into text and then that text is then
transmitted to the morse code conversion layer where the morse code of the
corresponding speech is given as the output. The accuracy of the model is
completely dependent on speech recognition, as the morse code conversion is a
process. The model is tested with recorded audio files with different
parameters. The proposed model's WER and accuracy are both determined to be
10.18% and 89.82%, respectively.