Multi-Dimensional Visualization for AMPER project

This Multi-Dimensional visualization is a Python-based visualization tool developed for the AMPER Project (Atlas Multimédia Prosodique de l'Espace Roman). It provides a holistic assessment of prosodic factors and structural features of intonation from a geo-variational perspective. By avoiding discrete simplifications, the script allows for the simultaneous and global examination of melodic modulations ($f_0$), intensity values, and vocalic durations.

How It Works

The pipeline translates three-dimensional prosodic data into a single, intuitive multidimensional space:

• $f_0$ (Melody): Represented by the base melodic curve.
• Intensity: Translated into variable line thickness; thicker segments indicate higher intensity.
• Vocalic Duration: Translated into color intensity; more intense/darker colors represent temporal contractions (faster speed), while softer/lighter colors indicate longer durations.

Key Features

• AMPER Database Integration: Specifically designed to read and process standard .txt files available in the BD-AMPER database.
• Comparative Superimposition: Enables the comparison of multiple intonation patterns at a single glance. This is particularly useful for identifying convergences and divergences between different pragmatic functions, such as declaratives (red) and interrogatives (blue).
• Rhythmic-Intonational Diagnostics: Helps researchers identify systematic accelerations, significant decelerations, and pre-pausal lengthening that might be missed in univariate plots.
• Geo-Prosodic Documentation: Supports the deep description of extensive intonational variation across the Romance language area without sacrificing generalizability.

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Requirements & Data

The tool is optimized for the data structures and research routines shared across the AMPER research network.

Software

• Python environment.
• Standard libraries for data processing and graphic rendering (e.g., Matplotlib).

Input Data

• Standard AMPER .txt files: The tool extracts intensity and vocalic interval durations directly from these files.

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Quick Start Guide

1. Prepare Your Data: Ensure your prosodic data is formatted as standard AMPER .txt files.
2. Run the Script: Load the Python routine to process the files and generate comparative graphics.
3. Interpret the Visuals:
   • Observe line thickness to locate energetic peaks.
   • Monitor color intensity to track speed; look for lighter colors to identify pre-pausal lengthening or specific movements in interrogative patterns.
4. Compare Functions: Superimpose different patterns to visualize how pragmatic functions (e.g., declarative vs. interrogative) differ across $f_0$, energy, and timing.

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Citation

If you use this tool in your research, please cite the presentation from the CIDS 2026 congress:

Lo Iacono, F., De Iacovo, V., & Romano, A. (2026). Describir a variación da entoación de xeito global: unha nova forma de visualizar os datos do proxecto AMPER. Congreso Internacional de Dialectoloxía e Sociolingüística (CIDS 2026), Santiago de Compostela.

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