Voice pathology detection refers to the process of identifying and diagnosing disorders or abnormalities in the human voice. These disorders can affect various aspects of vocal production, including pitch, loudness, quality, and resonance. Voice pathology detection typically involves the use of technology, such as digital signal processing, machine learning, and artificial intelligence, to analyze vocal recordings and detect any deviations from normal vocal patterns.

Some common voice pathologies include:

1. Hoarseness: Also known as dysphonia, hoarseness refers to a rough or raspy voice caused by irregular vibrations of the vocal cords. It can be a symptom of various underlying conditions, such as vocal cord nodules, laryngitis, or vocal cord paralysis.

2. Voice Tremor: Voice tremor is characterized by rhythmic fluctuations in pitch or amplitude during speech. It can be associated with neurological disorders such as Parkinson’s disease or essential tremor.

3. Vocal Fold Polyps or Nodules: Vocal fold polyps and nodules are noncancerous growths on the vocal cords that can cause changes in voice quality, including breathiness, roughness, or hoarseness.

4. Vocal Cord Paralysis: Vocal cord paralysis occurs when one or both vocal cords are unable to move properly, resulting in changes in voice quality, difficulty speaking, and swallowing problems.

Voice pathology detection systems aim to assist healthcare professionals in diagnosing voice disorders accurately and efficiently. By analyzing acoustic features of the voice, such as pitch, intensity, and spectral characteristics, these systems can provide objective measurements and indicators of vocal health. They can also be used for screening purposes, monitoring treatment progress, and guiding therapeutic interventions for individuals with voice disorders.