Domain specific voice intent classification with BLSTM
dc.contributor.advisor | Uthayasanker T | |
dc.contributor.author | Hellarawa HMMJ | |
dc.date.accept | 2022 | |
dc.date.accessioned | 2022 | |
dc.date.available | 2022 | |
dc.date.issued | 2022 | |
dc.description.abstract | With the current global pandemic all countries around the globe are facing difficulties managing their healthcare services in a way that ensures the high availability of critical services while maintaining the safety of both the patient and the staff. According to Gartner’s top 10 strategic technology trends 2021 [1], it says “Rather than building a technology stack and then exploring the potential applications, organizations must consider the business and human context first.” where it highlights the need for human centric development while stating that it is the IT leaders that decides what combination of the trends to involve in driving the most innovation and strategy. A decade ago, simply having a website was enough to impress prospective customers and help them find their way to a service or information need and to establish a brand loyalty or identity. The growth of the technology is demanding more innovative strategies to adopted to every small to large industries that are at any stage of maturity of their roadmap to success. The increasing demands of the clients and the ability to keep a loyal customer base has highlighted the need of having a more natural way of handling a customer’s inquiry gives a competitive advantage for any business. The disappointment due to a customer getting added to a call waiting queues to reach a particular service is very critical and can even cause a loss of business opportunity. Understanding call intents can help a service provider to adapt the business engagement with the outside in a way that customers are positively satisfied which could in return increases the sales revenue. Not only that, but indirectly enables the ability for business to allocation agents or help-desk staff optimally thus avoid understaffing and overstaffing situation, which are indirect costs for any revenue-based figure. Automation is where the technology is used to automate tasks that once required humans. Here, the menu-based call center automations can be taken as a replacement to the legacy call center agent where the human tasks were replaced by automation. The concept of hyperautomation is where the businesses are rapidly adopting it’s revenue-based processes and IT process for automation. And the current state-of-the-art deals with lot of advanced technologies like Machine Learning (ML) and Artificial Intelligence (AI). Where AI and ML are used for extending the capabilities of automations. | en_US |
dc.identifier.accno | TH4933 | en_US |
dc.identifier.citation | Hellarawa, H.M.M.J. (2022). Domain specific voice intent classification with BLSTM [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/22390 | |
dc.identifier.degree | MSc in Computer Science & Engineering | en_US |
dc.identifier.department | Department of Computer Science & Engineering | en_US |
dc.identifier.faculty | Engineering | en_US |
dc.identifier.uri | http://dl.lib.uom.lk/handle/123/22390 | |
dc.language.iso | en | en_US |
dc.subject | VOICE INTENT CLASSIFICATION | en_US |
dc.subject | HEALTHCARE | en_US |
dc.subject | BIDIRECTIONAL LONG SHORT-TERM MEMORY (BLSTM) | en_US |
dc.subject | SPEECH RECOGNITION | en_US |
dc.subject | COMPUTER SCIENCE & ENGINEERING - Dissertation | en_US |
dc.subject | COMPUTER SCIENCE- Dissertation | en_US |
dc.title | Domain specific voice intent classification with BLSTM | en_US |
dc.type | Thesis-Abstract | en_US |
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