VuVoPy 1.0.0

Voice features

VuVoPy

🎙️ VuVoPy — Voice Utility Library for Speech Parametrization A Python library for extracting acoustic features from speech signals, specifically developed for biomedical voice analysis and Parkinson’s disease research.

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📦 Installation

Install VuVoPy with pip:

pip install VuVoPy

📚 Documentation The full documentation is hosted on Read the Docs: 👉 https://vuvopy-documentation.readthedocs.io

Includes:

• 📦 Module overviews
• 📊 Feature extraction functions
• 🧠 Usage examples
• 🛠 Developer reference

🔬 Features

• durmad — Duration of voiced segments (mean absolute deviation)
• durmed — Duration of voiced segments (median)
• duv — Percentage of unvoiced frames
• hnr — Harmonics-to-noise ratio
• jitterPPQ — Pitch perturbation quotient (jitter)
• shimmerAPQ — Amplitude perturbation quotient (shimmer)
• mpt — Maximum phonation time
• ppr — Pitch period ratio
• relF0SD — Relative standard deviation of F0
• relF1SD, relF2SD — Relative deviation of formants F1 and F2
• relSEOSD — Relative deviation at sentence ends
• spir — Silence-to-phonation ratio

Getting Started

Import VuVoPy and run a feature extraction function:

python import VuVoPy as vp value = vp.durmad("my_signal.wav")

🧠 Example: Compute Speech Parameters

import VuVoPy as vp
import pandas as pd

file_path = "signal.wav"

durmad = vp.durmad(file_path, winlen=512, winover=256, wintype='hamm')
durmed = vp.durmed(file_path, winlen=512, winover=256, wintype='hamm')
duv = vp.duv(file_path, winlen=512, winover=256, wintype='hamm')
hnr = vp.hnr(file_path)
jitter = vp.jitterPPQ(file_path)
mpt = vp.mpt(file_path, winlen=512, winover=256, wintype='hamm')
ppr = vp.ppr(file_path, winlen=512, winover=256, wintype='hamm')
relf0sd = vp.relF0SD(file_path)
relf1sd = vp.relF1SD(file_path, winlen=512, winover=256, wintype='hamm')
relf2sd = vp.relF2SD(file_path)
relseosd = vp.relSEOSD(file_path, winlen=512, winover=256, wintype='hamm')
shimmer = vp.shimmerAPQ(file_path)
spir = vp.spir(file_path, winlen=512, winover=256, wintype='hamm')

data = {
    "durmad": [durmad],
    "durmed": [durmed],
    "duv": [duv],
    "hnr": [hnr],
    "jitter": [jitter],
    "mpt": [mpt],
    "ppr": [ppr],
    "relf0sd": [relf0sd],
    "relf1sd": [relf1sd],
    "relf2sd": [relf2sd],
    "relseosd": [relseosd],
    "shimmer": [shimmer],
    "spir": [spir]
}

df = pd.DataFrame(data)
print(df)