Voice Activation Systems for Embedded Devices: Systematic Literature Review

Abstract

A large number of modern mobile devices, embedded devices and smart home devices are equipped with a voice control. Automatic recognition of the entire audio stream, however, is undesirable for the reasons of the resource consumption and privacy. Therefore, most of these devices use a voice activation system, whose task is to find the specified in advance word or phrase in the audio stream (for example, Ok, Google) and to activate the voice request processing system when it is found. The voice activation system must have the following properties: high accuracy, ability to work entirely on the device (without using remote servers), consumption of a small amount of resources (primarily CPU and RAM), noise resistance and variability of speech, as well as a small delay between the pronunciation of the key phrase and the system activation. This work is a systematic literature review on voice activation systems that satisfy the above properties. We describe the principle of various voice activation systems' operation, the characteristic representation of sound in such systems, consider in detail the acoustic modelling and, finally, describe the approaches used to assess the models' quality. In addition, we point to a number of open questions in this problem.

Research on Estimation of Paddy Field Area Index Based on UAV Remote Sensing Images

“…Present 7% of error by implementing time series normalized difference vegetation index which is obtained from MODIS. The authors in [22] presented a new approach for estimating the crop yield through to the temperature vegetation dryness index by computing the RMSE coefficients in range between 10% to 14% for soybean and 15% to 23% for wheat.…”

Unsupervised Pre-Training for Voice Activation

“…The authors compared multilingual bottleneck features of the model, trained on well-resourced, but out-of-domain languages, and a correspondence autoencoder trained in a zero-resource fashion, as well as their combination. They found that this combination improves the quality of the voice activation system compared to the Mel-frequency cepstral coefficients (MFCC), which are widely used in ASR and voice activation [1].…”

“…The log-Mel filter banks features are often chosen for building voice activation or speech recognition systems [1,32]. We used the kaldi [33] implementation of feature computation with the following parameters: frame width-25 ms, frame shift-10 ms, number of bins-80.…”

“…Voice activation systems solve the task of finding predefined keywords or keyphrases in an audio stream [1]. This task has attracted both researchers and industry for decades.…”

Improving the effectiveness of voice activation systems with machine learning methods

“…Siūloma tipinės balso aktyvavimo sistemos apžvalga ir struktūra buvo paskelbta tarptautiniame mokslo žurnale (Kolesau & Šešok, 2020c).…”