Evidence-based guides on acoustic voice analysis for speech-language pathologists
Not every voice question needs every parameter. Learn which acoustic measures to use for dysphonia screening, breathiness, roughness, strain, gender-affirming voice work, and telehealth—based on current evidence.
Master vocal tract resonances for clinical practice. Learn F1/F2/F3 interpretation, gender-affirming voice therapy applications, resonant voice mechanisms, vowel space area for dysarthria, Praat settings by speaker type, and when formant analysis adds value.
HNR measures signal clarity—the balance between periodic harmonics and aperiodic noise. Learn when it's the best predictor of breathiness, when it fails for severe dysphonia, how it compares to CPP, and practical interpretation guidelines.
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.
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