Guías basadas en evidencia sobre análisis acústico de voz para fonoaudiólogos
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.
How to interpret wideband and narrowband spectrograms for clinical voice assessment. Patterns, pathologies, and practical applications.
Maximum Phonation Time and Dysphonia Severity Index explained. Recording protocols, normative data, and practical interpretation for clinical practice.
Siempre estamos buscando temas que ayuden a los fonoaudiólogos en su práctica clínica.
Sugerir un tema →Dr. Jorge C. Lucero
Profesor de Ciencias de la Computación, Universidad de Brasilia
El Dr. Lucero tiene más de 30 años de experiencia investigando la producción de voz y la dinámica de los pliegues vocales. Ha publicado más de 50 artículos revisados por pares sobre ciencia de la voz y desarrolló SimuVox, una herramienta de síntesis de voz basada en física. Su objetivo con PhonaLab es hacer que el análisis profesional de voz sea accesible para todos los profesionales.
Contenido Educativo: Esta guías tienen el fin educativo de apoyar la práctica clínica basada en evidencia. El contenido no pretende ser consejo médico. Las decisiones clínicas deben ser tomadas por profesionales de la salud calificados basándose en la evaluación individual del paciente.