Amelia Foster
Acoustic Phonetics Researcher & Voice Analysis Educator | Founder, VoiceFrequencyTest.com
Most people have heard their voice played back on a recording and thought it sounded wrong. What they are hearing — and struggling to reconcile — is the actual fundamental frequency of their voice, stripped of the bone conduction and resonance their skull adds when they speak. That gap between perceived voice and measured voice is the problem VoiceFrequencyTest.com was built to close.
My name is Amelia Foster. I have spent years studying how the human voice produces frequency, how those frequencies are detected and analysed, and why so many browser-based voice tools either get the science wrong or fail to explain what their numbers mean. The fundamental frequency of the human voice — the rate at which the vocal folds vibrate, measured in Hz — is one of the most precisely measurable characteristics of human sound production. A typical adult female speaking voice sits between 165 and 255 Hz. A typical adult male speaking voice sits between 85 and 180 Hz. These are not rough estimates — they are well-documented ranges from acoustic phonetics research, and they are the reference framework behind everything on this site.
The problem I kept encountering was tools that displayed a frequency number in real time with no explanation of what that number meant, no context for whether it was normal, and no account of what the tool was actually detecting versus what the user assumed it was detecting. VoiceFrequencyTest.com exists to do all three of those things correctly. To understand exactly how the frequency analysis works, see the How It Works page.
What I Research and Write About
Fundamental Frequency and Vocal Fold Physiology The fundamental frequency (F0) of a voice is produced by the periodic vibration of the vocal folds under subglottal air pressure. F0 is determined by vocal fold mass, length, and tension — all of which vary between individuals and change with age, hydration, and vocal training. I research how these physiological variables produce the frequency distributions we observe in different speaker populations, and how browser-based FFT analysis captures and represents them.
Acoustic Phonetics and Formant Analysis F0 is only one component of a voice’s frequency profile. Formants — resonant frequencies of the vocal tract — shape the timbre and intelligibility of speech above and around the fundamental. F1 and F2 formant frequencies are particularly significant in vowel identification and voice quality analysis. I write about how formant structure relates to fundamental frequency and what voice analysis tools can and cannot reveal about vocal tract resonance.
Pitch Detection Algorithms — FFT and YIN Two primary methods are used for real-time fundamental frequency detection in browser environments: Fast Fourier Transform (FFT) analysis, which identifies the strongest frequency component in the spectrum, and the YIN algorithm, which uses autocorrelation to identify the true fundamental even when higher harmonics are stronger than the fundamental in the spectrum. Understanding which algorithm a tool uses — and what its failure modes are — is essential to interpreting results correctly. The FAQ addresses the most common questions about what the tool detects and why results sometimes differ from expectations.
Voice Type Classification and Frequency Ranges Voice type classification — soprano, mezzo-soprano, alto, tenor, baritone, bass — is based on a combination of range, timbre, and register transition points called passaggi. Fundamental frequency alone does not determine voice type, but it is a measurable and informative starting point. I write about the relationship between measured F0 ranges and traditional voice classification, and where browser-based tools can contribute to and where they fall short of a full vocal assessment.
Why I Built This
When I was researching voice frequency analysis tools available to non-specialist users, I found a consistent pattern: tools that showed a number but explained nothing, or tools that explained the concept of pitch but made no distinction between fundamental frequency and perceived pitch — two related but distinct things. A voice can have a fundamental frequency of 130 Hz while sounding higher to a listener because of prominent upper harmonics.
What I could not find was a tool that measured F0 accurately in real time, displayed it clearly in Hz with its corresponding musical note, and provided enough context — typical ranges by gender and age, the role of harmonics, the difference between speaking F0 and singing F0 — for a user without a music or science background to understand what they were looking at.
That gap is what VoiceFrequencyTest.com was built to fill.
Accuracy Standards
Every frequency range, algorithm description, and voice science claim on VoiceFrequencyTest.com is cross-referenced against published acoustic phonetics literature and the W3C Web Audio API specification. Speaking fundamental frequency ranges cited on this site are drawn from peer-reviewed research in acoustic phonetics. Pitch detection algorithm behaviour is documented against the Web Audio API specification and the original YIN algorithm paper (de Cheveigné and Kawahara, 2002). Limitations — including the effect of background noise, microphone frequency response, and OS audio processing on F0 detection accuracy — are stated explicitly on every relevant page. For how your data is handled during analysis, see the Data Security page.
Tools on This Site
- Voice Frequency Test — voicefrequencytest.com
Get in Touch
For content corrections, technical questions, or data requests, visit the Contact page or email directly: contact@voicefrequencytest.com
Response times: technical and content questions within 48–72 hours. Privacy and data requests within 7 business days. GDPR requests within 30 days. CCPA requests within 45 days.
Amelia Foster is the founder and sole author of VoiceFrequencyTest.com. For a full account of how content is researched and written, see the Editorial Guidelines. Last updated: June 2026.