An Email to Readable Vietnamese Text Conversion Algorithm for Use in TTS Application

In recent years, the growth of corporates’ businesses worldwide has driven the setups of call centers for supporting global customers 24/7 across the globe. However, many of the call centers are operated by human manually. Thus, there is need for developing automatic call center which is powered by artificial intelligence (AI), hence reducing operational costs through automation of calls, answering calls, conducting surveys, and receiving customer feedbacks. In this context, recently developed engines such as FPT.AI serves well local customers since it supports well the national language. However, it’s text-to-speech (TTS), an essential part of the complete engine, is currently having difficulties in reading customer emails. Therefore, this work presents an email to readable Vietnamese text conversion algorithm for use in TTS application. The average processing time tested on 60 emails is 1.7 milliseconds (ms). By manually validating the dataset, it is found that the algorithm achieves accuracy of up to 86.67%.

[1]  Tran Duc Chung,et al.  A Question Detection Algorithm for Text Analysis , 2020, ICIIT.

[2]  Ali Selamat,et al.  An evaluation on the efficiency of hybrid feature selection in spam email classification , 2015, 2015 International Conference on Computer, Communications, and Control Technology (I4CT).

[3]  Tarun Kumar,et al.  Email Spam Detection Using Integrated Approach of Naïve Bayes and Particle Swarm Optimization , 2018, 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS).

[4]  Sudhir N. Dhage,et al.  Survey on Virtual Assistant: Google Assistant, Siri, Cortana, Alexa , 2018, Communications in Computer and Information Science.

[5]  Alberto Bacchelli,et al.  Content classification of development emails , 2012, 2012 34th International Conference on Software Engineering (ICSE).

[6]  Bansi R. Savaliya,et al.  Email fraud detection by identifying email sender , 2017, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS).

[7]  Jose M. Garcia-Bravo,et al.  Voice Activated Semi-Autonomous Vehicle Using Off the Shelf Home Automation Hardware , 2018, IEEE Internet of Things Journal.

[8]  Duc Chung Tran.  The First Vietnamese FOSD-Tacotron-2-based Text-to-Speech Model Dataset , 2020, Data in brief.

[9]  Micheal Drieberg,et al.  End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application , 2020, 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech).

[10]  Xiaolong Wang,et al.  Content-Oriented User Modeling for Personalized Response Ranking in Chatbots , 2018, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[11]  José M. F. Moura,et al.  Visual Dialog , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Alexandra Cernian,et al.  The design and validation of an automatic email clustering system based on semantics , 2011, Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems.