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Writer's pictureMai Ling Chan

Could This New Approach Revolutionize AI in Speech Therapy?

digitally created image a mouth with tech code behind it. Text reads: Could this new approach revolutionize AI in speech therapy.

The intersection of artificial intelligence (AI) and speech therapy is rapidly evolving, promising innovative solutions for diagnosis and treatment. As a speech therapist passionate about technology, I am also watching for updates on how these advancements can enhance our practice. Keeping in mind that it is crucial that we approach AI integration thoughtfully, ensuring that new technologies are not only "sexy" and "cutting-edge" but also effective and ethical.


A New Framework for AI in Speech Therapy

This is why I am excited to share a new foundational framework recently published by Dr. Julie Liss—one of my favorite professors during my graduate studies at Arizona State University—and her co-author Visar Berisha. This framework offers valuable guidance for developing AI models to support speech therapy.


Categorizing Health Conditions for Highly Targeted Therapy

The framework introduces a novel approach to categorizing health conditions based on their effects on speech for example:

  1. Articulation: How conditions impact the physical production of speech sounds

  2. Phonation: The effects on vocal cord function and voice quality

  3. Resonance: Changes in the way sound resonates in the vocal tract


The framework's structured approach to categorizing speech-related health conditions provides a clear path for developing AI technologies that are more targeted and effective. By understanding the specific impacts of different conditions on speech production mechanisms, developers can create AI models that are finely tuned to detect and monitor these changes. This leads to more accurate diagnostics and personalized treatment plans, ultimately improving patient outcomes.

Challenges and Potentials in Speech-Based Diagnostics

Dr. Liss and Berisha highlight both the challenges and potential of the current methology of utilizing AI to analyze speech patterns as biomarkers for various disorders. For example:

  • Early detection of Alzheimer's disease through subtle changes in speech patterns

  • Identifying mood disorders like depression by analyzing vocal characteristics

  • Monitoring Parkinson's disease progression through changes in articulation and phonation

These applications demonstrate how AI could provide non-invasive, cost-effective diagnostic tools that significantly improve intervention strategies.


However, several challenges remain:

  • Limited Clinical Datasets: Small datasets may lead to overfitting and poor generalization.

  • Model Complexity: Lack of interpretability hinders troubleshooting and improvement.

  • Privacy Concerns: Ensuring data security and regulatory compliance is crucial.

  • Feasibility Issues: Complex relationships between speech and health limit model accuracy.


Addressing these challenges is key to harnessing AI's full potential in speech therapy. Combining speech science with clinical expertise can help develop robust models for real-world clinical settings.

Bridging Speech Science and Clinical Research

The research emphasizes the importance of combining speech science with clinical expertise to develop more robust AI models. This collaboration could lead to faster, more effective development of tools that perform well not just in controlled tests, but also in real-world clinical settings.

Ethical Considerations in AI Implementation

While the potential of AI in speech therapy is immense, the article also stresses the critical need to protect patients from bias and ensure privacy. As we integrate AI into clinical practice, we must prioritize:

  • Developing fair and unbiased algorithms

  • Safeguarding patient privacy

  • Maintaining high ethical standards in healthcare


The Future of AI in Speech Therapy

Dr. Julie Liss's contributions to this field continue to inspire advancements in speech therapy. By integrating AI with clinical expertise, we can drive the development of speech-based biomarkers, potentially revolutionizing health assessments and making care more accessible and effective for diverse populations.

What's Next?

As we stand at the beginnings of this technological revolution in speech therapy, it's crucial that we as practitioners stay informed and engaged. How do you envision AI enhancing your practice? What ethical considerations do you think are most pressing as we move forward?

Stay tuned for more updates on how AI is transforming the landscape of speech therapy, enhancing both diagnostic accuracy and patient outcomes. Together, we can shape a future where technology and human expertise combine to provide the best possible care for our patients.


Follow me for more AI, Speech Therapy, API, Disability Advocacy and Entrepreneurship, and AAC insights and info.

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