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4 مستودعات

Awesome GitHub RepositoriesSpectrogram Generation

Visualizing audio frequencies over time using color-mapped spectrograms.

Distinct from Frequency Analyzers: Focuses on the visual spectrogram output rather than the raw counting logic of a frequency analyzer.

Explore 4 awesome GitHub repositories matching data & databases · Spectrogram Generation. Refine with filters or upvote what's useful.

Awesome Spectrogram Generation GitHub Repositories

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  • katspaugh/wavesurfer.jsالصورة الرمزية لـ katspaugh

    katspaugh/wavesurfer.js

    10,114عرض على GitHub↗

    wavesurfer.js is a WebAudio playback library and interactive waveform visualizer that renders audio data onto an HTML5 canvas. It enables users to see and navigate sound files through a visual representation of audio peaks, allowing for direct seeking and playback control within a web browser. The project is distinguished by its flexible rendering model, which can use precomputed peak data to display waveforms without downloading or decoding the full audio file. It utilizes a plugin-based extension model to integrate advanced tools such as spectrograms, interactive audio timelines, and real-t

    Generates a color-mapped spectrogram showing how audio frequencies change over time.

    TypeScriptaudiojavascriptmusic
    عرض على GitHub↗10,114
  • tstack/lnavالصورة الرمزية لـ tstack

    tstack/lnav

    9,630عرض على GitHub↗

    lnav is a terminal-based log viewer and analyzer designed for aggregating, filtering, and analyzing multiple log files in a single chronological view. It functions as a console application that can replace the system pager, providing syntax highlighting and document navigation for system or application logs. The project distinguishes itself by mapping unstructured log data to virtual SQLite tables, enabling the use of SQL and PRQL for structured data analysis, aggregations, and relational queries. It further differentiates its capability set through native integration for retrieving and taili

    Generates a spectrogram to visualize the distribution of values within a numeric log message field.

    C++command-line-toollesslog-analysis
    عرض على GitHub↗9,630
  • makcedward/nlpaugالصورة الرمزية لـ makcedward

    makcedward/nlpaug

    4,658عرض على GitHub↗

    nlpaug is a data augmentation library designed to generate synthetic text, audio, and spectrogram data to improve the robustness of machine learning models. It functions as a textual data synthesizer and an audio signal augmentor, providing specialized tools to expand datasets through various transformation methods. The project distinguishes itself through its ability to orchestrate complex workflows using a pipeline orchestrator, which allows multiple augmentation functions to be chained together sequentially or randomly. It supports sophisticated text synthesis via back-translation, context

    Transforms audio spectrograms using time and frequency masking to improve speech recognition robustness.

    Jupyter Notebook
    عرض على GitHub↗4,658
  • miek/inspectrumالصورة الرمزية لـ miek

    miek/inspectrum

    2,466عرض على GitHub↗

    Displays a time-frequency heatmap of captured radio signals with zoom, pan, and measurement capabilities.

    C++dspsdr
    عرض على GitHub↗2,466
  1. Home
  2. Data & Databases
  3. Frequency Analyzers
  4. Spectrogram Generation

استكشف الوسوم الفرعية

  • Frequency MaskingHiding specific time or frequency strips in spectrograms to improve model robustness. **Distinct from Spectrogram Generation:** Distinct from Spectrogram Generation: focuses on the modification/masking of existing spectrograms for ML training, not the generation of the visual itself.
  • Numeric Field SpectrogramsVisualizing the distribution of numeric log field values over time using spectrograms. **Distinct from Spectrogram Generation:** Applies spectrogram visualization to numeric log data rather than audio frequencies.
  • SDR Spectrogram AnalyzersDesktop tools that display a time-frequency heatmap of captured radio signals with zoom, pan, and measurement capabilities. **Distinct from Spectrogram Generation:** Distinct from Spectrogram Generation: adds SDR-specific signal analysis and measurement, not just audio spectrogram visualization.
  • Spectrogram MaskingApplying time and frequency masking to audio spectrograms to increase robustness in speech recognition models. **Distinct from Spectrogram Generation:** Distinct from Spectrogram Generation: focuses on the masking operation for augmentation, not the visualization process.