Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing

By Y. Jung, S. Hong, Hee Seung Wang, J. Han, Trung X. Pham, Hyunsin Park, Junyeong Kim, Sunghun Kang, Chang-Dong Yoo, K. Lee. Advances in Materials, 2019

307 citations recorded by the source corpus.

Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine learning software will play an innovative interface for artificial intelligence (AI) services. Collaboration and novel approaches between both smart sensors and speech algorithms should be attempted to realize a hyperconnected society, which can offer personalized services such as biometric authentication, AI secretaries, and home appliances. Here, representative developments in speech recognition are reviewed in terms of flexible piezoelectric materials, self‐powered sensors, machine learning algorithms, and speaker recognition.

Subfields: Biomedical Engineering, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/a58c6faef2859fa62401dd22c90a9d04102bc206

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Xinge Guo
2. Chengkuo Lee
3. Tianyiyi He
4. Zhongda Sun
5. Qiongfeng Shi
6. Bowei Dong
7. Jianxiong Zhu
8. Long Liu

In Cognitive Neuroscience

1. Chengkuo Lee
2. Xinge Guo
3. Tianyiyi He
4. Qiongfeng Shi
5. Jianxiong Zhu
6. Bowei Dong
7. Zhongda Sun
8. Long Liu

Citations in the corpus

• Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses (2023, methodology): “Nowadays, machine learning has exhibited a remarkable significance in flexible electronics for data analysis, pattern recognition, and decision optimization, involving various fields such as medical diagnosis, health monitoring, human–machine interaction, and smart home [16, 19, 49].”
• Development Trends and Perspectives of Future Sensors and MEMS/NEMS (2019, methodology): “reported flexible piezoelectric acoustic sensors and machine learning for speech processing as shown in Figure 12d [186].”