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Frequency, Time, Representation and Modeling Aspects for Major Speech and Audio Processing Applications
Juraj Kacur1, Boris Puterka2, Jarmila Pavlovicova2
1Institute of Multimedia Information and Communication Technologies, Faculty of Electrical Engineering and Information Technology STU, 812 19 Bratislava, Slovakia.
Sensors (Basel, Switzerland)
|August 26, 2022
Summary
This study shows that basic audio signal properties like frequency and time affect speech recognition, speaker recognition, and emotion recognition accuracy. Understanding these domain-dependent effects is crucial for optimizing audio processing systems, especially with limited resources.
Area of Science:
- Speech and Audio Signal Processing
- Machine Learning for Audio Analysis
Background:
- The growing number of speech and audio processing applications necessitates understanding signal property impacts.
- Different applications have unique requirements for audio signals and sensors.
- Basic physical properties of audio signals can influence application performance.
Purpose of the Study:
- To evaluate the effect of fundamental speech and audio signal properties on recognition accuracy.
- To analyze the impact of frequency ranges, time intervals, quantization, and model complexity.
- To determine how these effects vary across different audio processing domains.
Main Methods:
- Utilized domain-specific datasets for testing.
- Employed eligible feature extraction methods and complex neural network models.
- Tested and evaluated the influence of signal properties on accuracy for speech, speaker, emotion, and audio event recognition.
Main Results:
- Confirmed that basic audio signal parameters significantly affect overall performance.
- Demonstrated that the impact of these parameters is domain-dependent.
- Quantified the influence of frequency, time, quantization, and model complexity on recognition tasks.
Conclusions:
- Accurate knowledge of signal property effects is vital for system designers.
- This understanding aids in selecting appropriate hardware, sensors, and software, particularly under resource constraints.
- Tailoring signal processing strategies to specific application domains can enhance performance.
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