Performance comparison of wake-up-word detection on mobile devices using various convolutional neural networks

Sanghong Kim; Bowon Lee

doi:10.7776/ASK.2020.39.5.454

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2020 Vol.39, Issue 5 Preview Page Next Page

Research Article

Performance comparison of wake-up-word detection on mobile devices using various convolutional neural networks 다양한 합성곱 신경망 방식을 이용한 모바일 기기를 위한 시작 단어 검출의 성능 비교

30 September 2020. pp. 454-460

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Abstract

Artificial intelligence assistants that provide speech recognition operate through cloud-based voice recognition with high accuracy. In cloud-based speech recognition, Wake-Up-Word (WUW) detection plays an important role in activating devices on standby. In this paper, we compare the performance of Convolutional Neural Network (CNN)-based WUW detection models for mobile devices by using Google's speech commands dataset, using the spectrogram and mel-frequency cepstral coefficient features as inputs. The CNN models used in this paper are multi-layer perceptron, general convolutional neural network, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet. We also propose network that reduces the model size to 1/25 while maintaining the performance of MobileNet is also proposed.

Keywords

Performance comparison

Wake-up-word detection

Convolutional neural network

Artificial Intelligence (AI) assistant

음성인식 기능을 제공하는 인공지능 비서들은 정확도가 뛰어난 클라우드 기반의 음성인식을 통해 동작한다. 클라우드 기반의 음성인식에서 시작 단어 인식은 대기 중인 기기를 활성화하는 데 중요한 역할을 한다. 본 논문에서는 공개 데이터셋인 구글의 Speech Commands 데이터셋을 사용하여 스펙트로그램 및 멜-주파수 캡스트럼 계수 특징을 입력으로 하여 모바일 기기에 대응한 저 연산 시작 단어 검출을 위한 합성곱 신경망의 성능을 비교한다. 본 논문에서 사용한 합성곱 신경망은 다층 퍼셉트론, 일반적인 합성곱 신경망, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet이며, MobileNet의 성능을 유지하면서 모델 크기를 1/25로 줄인 네트워크도 제안한다.

키워드

성능 비교

시작 단어 검출

합성곱 신경망

인공지능 비서

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Information

Publisher :The Acoustical Society of Korea
Publisher(Ko) :한국음향학회
Journal Title :The Journal of the Acoustical Society of Korea
Journal Title(Ko) :한국음향학회지
Volume : 39
No :5
Pages :454-460
Received Date : 2020-05-21
Accepted Date : 2020-07-07
DOI :https://doi.org/10.7776/ASK.2020.39.5.454

The Journal of the Acoustical Society of Korea ISSN:1225-4428(Print) 2287-3775(Online) 한국음향학회지

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