@inproceedings{3b164ef5c6ce4c1791830444fe0c5c2c,
title = "Automatic Speech Recognition for Portuguese with Small Data Set",
abstract = "Voice recognition has become more and more popular in various systems and applications. To further promote Macau tourism worldwide, a mobile Macau tourism APP is being developing that supports voice control to facilitate Portuguese users. Consequently, this paper is about the research and implementation of an Automatic Speech Recognition (ASR) engine for Portuguese language. In this research, three well-known open-source ASR platforms were evaluated and compared. The complete ASR development procedure using Kaldi platform is discussed. Due to the limitation of collected voice data, a novel few-shot learning and transfer learning is implemented in this project. The final model achieved a stable 95.25% accuracy which is good enough for production use. The novel technics implemented in this research can be used for ASR trainings with limited training data and can be extended to a wide range of applications in the future.",
keywords = "ASR, Few-shot learning, Portuguese voice recognition, Transfer learning",
author = "Yapeng Wang and Ruize Jia and Lam, {Chan Tong} and Choi, {Ka Cheng} and Ng, {Koon Kei} and Xu Yang and Im, {Sio Kei}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st IEEE/ACIS International Fall Virtual Conference on Computer and Information Science, ICIS 2021 ; Conference date: 13-10-2021 Through 15-10-2021",
year = "2022",
doi = "10.1007/978-3-030-90528-6_1",
language = "English",
isbn = "9783030905279",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1--13",
editor = "Roger Lee",
booktitle = "Computer and Information Science 2021 - Fall",
address = "Germany",
}