ArticleScientific reports2023
Towards interpretable speech biomarkers: exploring MFCCs.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Explainable and Interpretable AI for Voice and Speech Analysis in Clinical Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Voice features in paediatric ADHD: baseline group differences and longitudinal change under methylphenidate.European child & adolescent psychiatry · 2026Article
- Towards a Compositional Framework for Describing Human Phenotypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Decoding Gender in Cough Sounds: A Transformer-Based Analysis.The Laryngoscope · 2026Article
- A cough sound-based deep learning algorithm for accessible prompt detection of chronic obstructive pulmonary disease with smartphones.NPJ primary care respiratory medicine · 2026Article
- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- Noninvasive prescreening of pediatric adenoid hypertrophy using quantified MFCC statistics and clinical features: development and external validation.Frontiers in bioengineering and biotechnology · 2026Article
- What can speech tell us about pain?Pain reports · 2025Article
- A generalizable and open-source algorithm for real-life monitoring of tremor in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning.Brain sciences · 2025Article
- Optimal feature selection and model explanation for reef fish sound classification.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.BMC psychiatry · 2025Article
- Longitudinal voice monitoring in a decentralized Bring Your Own Device trial for respiratory illness detection.NPJ digital medicine · 2025Article
- Developing digital health technologies for frontotemporal degeneration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Associations of Vocal Features, Psychiatric Symptoms, and Cognitive Functions in Schizophrenia.Neuropsychiatric disease and treatment · 2025Article
- Development and validation of a nomogram for predicting lung cancer based on acoustic-clinical features.Frontiers in medicine · 2025Article
- Analyzing Wav2Vec 1.0 Embeddings for Cross-Database Parkinson's Disease Detection and Speech Features Extraction.Sensors (Basel, Switzerland) · 2024Article
- Exploring the Relationships Between Antipsychotic Dosage and Voice Characteristics in Relation to Extrapyramidal Symptoms.Psychiatry investigation · 2024Article
- Sound as a bell: a deep learning approach for health status classification through speech acoustic biomarkers.Chinese medicine · 2024Article
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Authors and funding
10 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are regarded as uninterpretable. Here we explore correlations between MFCC coefficients and more interpretable speech biomarkers. In particular we quantify the MFCC2 endpoint, which can be interpreted as a weighted ratio of low- to high-frequency energy, a concept which has been previously linked to disease-induced voice changes. By exploring MFCC2 in several datasets, we show how its sensitivity to disease can be increased by adjusting computation parameters.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.