Evidence-based guides on acoustic voice analysis for speech-language pathologists
The voice reveals more than voice quality—emerging research shows acoustic biomarkers can detect early cognitive impairment with up to 89% accuracy. Learn which parameters matter, current validation status, and what this means for speech pathologists as AI-driven screening approaches clinical deployment.
The spectrogram is the most powerful visual tool in voice assessment—but many clinicians find it intimidating. Learn wideband vs narrowband analysis, Titze's voice signal typing (Types 1-4), and how to read harmonic patterns, breathiness, roughness, and pathology indicators.
Traditional acoustic measures ask explicit questions. AI models ask implicit ones—learned from data, encoded in training. As AI enters clinical voice assessment, understanding what question a model is actually asking becomes the central challenge.
F0 explains only 42% of perceived gender—resonance, intonation, and speech patterns account for the rest. Learn evidence-based pitch targets (180 Hz threshold), why formants require 20% elevation, hormone effects, WPATH SOC-8 guidelines, and how to track progress with acoustic measures.
Traditional perturbation measures aren't obsolete—but they have critical limitations. Learn when jitter and shimmer are valid, when they fail (severe dysphonia), why ASHA now recommends CPP as primary, and how Praat vs MDVP give different values.
Can you trust voice recordings from a smartphone? The Bridge2AI-Voice Consortium and 2020-2025 validation studies reveal which parameters work (F0, CPP) and which don't (shimmer, HNR). Learn the evidence-based protocols that make smartphone recordings clinically valid.
Single acoustic parameters can't capture the full complexity of voice quality. Learn how AVQI and ABI combine multiple measures into validated scores that correlate with perceptual ratings, plus validated cutoffs for Brazilian Portuguese.
CPP has emerged as the most reliable acoustic measure for detecting dysphonia. Learn why researchers and clinicians are moving beyond traditional jitter/shimmer measurements, and how to interpret CPP values in your clinical practice.
Maximum Phonation Time and Dysphonia Severity Index explained. Recording protocols, normative data, and practical interpretation for clinical practice.
We're always looking for topics that would help voice clinicians in their practice.
Suggest a topic →Dr. Jorge C. Lucero
Professor of Computer Science, University of Brasília
Dr. Lucero has over 30 years of experience researching voice production and vocal fold dynamics. He has published 50+ peer-reviewed papers on voice science and developed SimuVox, a physics-based voice synthesis tool. His goal with PhonaLab is to make professional voice analysis accessible to all clinicians.
Educational Content: Articles on this pages are provided for educational purposes to support evidence-based clinical practice. Content is not intended as medical advice. Clinical decisions should be made by qualified healthcare professionals based on individual patient assessment.