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Li, K., Mao, S., Li, X., Wu, Z. and Meng, H. (2018) Automatic Lexical Stress and Pitch Accent Detection for L2 English Speech Using Multi-Distribution Deep Neural Networks. Speech Communication, 96, 28-36.
https://doi.org/10.1016/j.specom.2017.11.003

has been cited by the following article:

• TITLE: An Overview of Basics Speech Recognition and Autonomous Approach for Smart Home IOT Low Power Devices

  AUTHORS: Jean-Yves Fourniols, Nadim Nasreddine, Christophe Escriba, Pascal Acco, Julien Roux, Georges Soto Romero

  KEYWORDS: Voice Recognition, Speech Processing, Voice Command, Embedded Device

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.9 No.4, October 30, 2018

  ABSTRACT: Automatic speech recognition, often incorrectly called voice recognition, is a computer based software technique that analyzes audio signals captured by a microphone and translates them into machine interpreted text. Speech processing is based on techniques that need local CPU or cloud computing with an Internet link. An activation word starts the uplink; “OK google”, “Alexa”, … and voice analysis is not usually suitable for autonomous limited CPU system (16 bits microcontroller) with low energy. To achieve this realization, this paper presents specific techniques and details an efficiency voice command method compatible with an embedded IOT low-power device.