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CONVOLUTIONAL RECURRENT NEURAL NETWORK BASED DIRECTION OF ARRIVAL ESTIMATION METHOD USING TWO MICROPHONES FOR HEARING

Abdullah Küçük¹, Issa M S Panahi¹

¹The University of Texas at Dallas Department of Electrical and Computer Engineering, 800 West Campbell Richardson, TX 75080, USA.

IEEE International Workshop on Machine Learning for Signal Processing : [Proceedings]. IEEE International Workshop on Machine Learning for Signal Processing

|May 11, 2021

Summary

This study introduces a smartphone app using a convolutional recurrent neural network (CRNN) for accurate direction of arrival (DOA) angle estimation. This technology enhances hearing aid applications by visually indicating sound sources for users with hearing loss.

Keywords:

Speech source localization convolutional recurrent neural network real-time inference two microphone DOA

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Area of Science:

Signal Processing
Machine Learning
Assistive Technology

Background:

Hearing disorders significantly impact communication.
Existing hearing aid technology can be improved with better sound localization.
Direction of Arrival (DOA) estimation is crucial for spatial audio perception.

Purpose of the Study:

To develop a Convolutional Recurrent Neural Network (CRNN) based DOA angle estimation method.
To implement this method on Android smartphones for hearing aid applications.
To provide a visual indication of sound source direction for hearing-impaired individuals.

Main Methods:

Utilized the real and imaginary parts of the Short-Time Fourier Transform (STFT) as features.
Implemented a CRNN architecture for DOA angle estimation.
Performed real-time inference using only two built-in smartphone microphones.

Main Results:

Achieved an accuracy of 87.33% for unseen environments.
Demonstrated real-time performance on Android smartphones.
Validated the generalization and robustness of the CRNN model through real-time implementation.

Conclusions:

The proposed CRNN-based DOA estimation method is effective for hearing aid applications.
Smartphone implementation offers a practical and accessible solution for improving hearing.
The method shows promise for enhancing spatial awareness in individuals with hearing loss.