7 repository-uri
Tools that generate frequency-based heat maps to analyze audio content over time.
Distinct from Audio Visualization Tools: Specifically focuses on the generation of spectrograms rather than general audio visualization or feature extraction.
Explore 7 awesome GitHub repositories matching graphics & multimedia · Spectrogram Renderers. Refine with filters or upvote what's useful.
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
Includes a dedicated spectrogram renderer that generates frequency heat maps for audio analysis.
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
Generates mel spectrogram plots to visualize and compare predicted audio quality against target speech signals.
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
Analyzes spectrograms to identify peak energy points, creating unique digital signatures for audio tracks.
nlpaug este o bibliotecă de augmentare a datelor concepută pentru a genera text sintetic, audio și date de spectrogramă, cu scopul de a îmbunătăți robustețea modelelor de machine learning. Funcționează ca un sintetizator de date textuale și un augmentator de semnal audio, oferind instrumente specializate pentru extinderea seturilor de date prin diverse metode de transformare. Proiectul se distinge prin capacitatea de a orchestra fluxuri de lucru complexe folosind un orchestrator de pipeline, care permite înlănțuirea mai multor funcții de augmentare secvențial sau aleatoriu. Suportă sinteza sofisticată de text prin back-translation, contextual word embeddings și integrarea modelelor de limbaj pre-antrenate, oferind în același timp augmentarea imaginilor de spectrogramă prin mascarea timpului și a frecvenței. Biblioteca acoperă o gamă largă de capabilități, inclusiv modificarea semnalului audio cu injectare de zgomot și pitch shifting, alterări de text bazate pe reguli pentru simularea greșelilor de scriere și extinderea seturilor de date prin generarea de propoziții și substituție semantică. Oferă, de asemenea, controale pentru volumul de augmentare și filtrarea țintei folosind expresii regulate pentru a proteja anumite token-uri de modificare.
Transforms audio spectrograms using time and frequency masking to improve speech recognition robustness.
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
Generates frequency-based heat maps to analyze audio content over time as spectrograms.
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
Includes a graphical interface to render audio spectrograms for revealing visually hidden patterns.
Divides the time-frequency display into cached image tiles recomputed only on zoom or pan changes.