Awesome GitHub RepositoriesSpectrogram Renderers

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

EmotiVoice is an emotional text-to-speech engine and bilingual speech synthesizer designed to generate synthetic audio in English and Chinese. It utilizes a deep learning architecture to produce high-fidelity speech with controllable emotional states and timbres. The project includes a voice cloning framework for replicating specific speaker identities by training custom acoustic models on personal audio datasets. It employs a jointly-trained acoustic-vocoder pipeline and style-embedding-based synthesis to manage expression and reduce audio artifacts. The system covers a broad range of speec

Dejavu is a Python audio fingerprinting library and recognition engine. It functions as a digital audio signature tool used to analyze sound waves and create unique identifiers for the purposes of audio search and retrieval. The project enables automatic music identification by matching live audio feeds or recorded clips against a database of fingerprints. It covers audio content matching and digital audio archiving to identify original source recordings from a stored collection. The system incorporates capabilities for generating audio fingerprints, identifying audio tracks, and recognizing

nlpaug ist eine Data-Augmentation-Bibliothek, die entwickelt wurde, um synthetische Text-, Audio- und Spektrogrammdaten zu generieren und die Robustheit von Machine-Learning-Modellen zu verbessern. Sie fungiert als Synthesizer für Textdaten und Augmenter für Audiosignale und bietet spezialisierte Tools, um Datensätze durch verschiedene Transformationsmethoden zu erweitern. Das Projekt zeichnet sich durch die Fähigkeit aus, komplexe Workflows mithilfe eines Pipeline-Orchestrators zu steuern, der es ermöglicht, mehrere Augmentationsfunktionen sequenziell oder zufällig zu verketten. Es unterstützt anspruchsvolle Textsynthese durch Back-Translation, kontextuelle Word-Embeddings und die Integration vortrainierter Sprachmodelle, während es gleichzeitig Spektrogramm-Bild-Augmentation durch Zeit- und Frequenzmaskierung bietet. Die Bibliothek deckt ein breites Spektrum an Funktionen ab, darunter die Modifikation von Audiosignalen mit Rausch-Injektion und Pitch-Shifting, regelbasierte Textänderungen zur Simulation von Tipp- und Rechtschreibfehlern sowie die Erweiterung von Datensätzen durch Satzgenerierung und semantische Substitution. Sie bietet zudem Kontrollen für das Augmentationsvolumen und die Zielfilterung mittels regulärer Ausdrücke, um bestimmte Tokens vor Modifikationen zu schützen.

Spek is an acoustic spectrum tool and audio frequency visualizer designed to decode audio streams and analyze their spectral density. It functions as an audio spectrogram analyzer that displays frequency distributions to help identify the sonic characteristics of audio files. The tool specifically includes capabilities as a lossy compression detector, allowing for the identification of encoding artifacts and frequency cut-offs caused by lossy transcoding. The software covers audio file inspection and spectral analysis, providing the ability to select individual audio streams and channels. Us

This project is a steganography analysis toolkit and digital forensics suite designed to detect, extract, and embed hidden data within image and audio files. It provides a dockerized security environment that bundles various analysis tools into a containerized workspace, including a media spectrogram visualizer for revealing visually hidden patterns. The toolkit features a dedicated brute force system for recovering password-protected messages using automated wordlists and candidate password testing. It distinguishes itself by providing rule-based wordlist generation that uses expansion patte