awesome-repositories.com
Blog
MCP
awesome-repositories.com

Découvrez les meilleurs dépôts open-source grâce à notre recherche par IA.

ExplorerRecherches sélectionnéesAlternatives open sourceLogiciels auto-hébergésBlogPlan du site
ProjetServeur MCPÀ proposNotre méthodologiePresse
Mentions légalesConfidentialitéConditions d'utilisation
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
jameslyons avatar

jameslyons/python_speech_features

0
View on GitHub↗
2,422 stars·609 forks·Python·MIT·11 vues

Python Speech Features

Python speech features is a signal processing toolkit and library for extracting standard speech recognition features from raw audio signals. It provides computational capabilities to calculate mel-frequency cepstral coefficients, raw and log filterbank energies, and spectral subband centroids for automated speech recognition systems and acoustic analysis.

The library implements audio signal transformations including pre-emphasis filtering, overlapping windowed frame segmentation, Fast Fourier Transform spectral analysis, mel-filterbank projection with configurable filter weights and frequency ranges, and discrete cosine transform cepstral projection.

Features

  • Audio Feature Extraction - Computes standard audio representations such as mel-frequency cepstral coefficients and filterbank energies from raw audio.
  • Mel-band Energy Extractions - Transforms audio frequency spectrums into perceptually-scaled filterbank energies using configurable mel-triangle filter weights.
  • Speech Recognition - Extracts standard audio representations like mel-frequency cepstral coefficients for speech recognition tasks.
  • Feature Extraction - Provides a signal processing toolkit for computing cepstral coefficients and filterbank energies for speech recognition.
  • Mel-Frequency Cepstral Coefficients - Applies a discrete cosine transform to convert log filterbank energies into cepstral coefficients.
  • Fourier Transforms - Converts windowed time-domain audio frames into frequency-domain power spectra using numerical Fourier transforms.
  • Spectral Centroids - Computes spectral subband centroids from audio signals to characterize frequency distribution.
  • Windowed Segmentation - Segments continuous audio waveforms into overlapping short-time frames using configurable window functions.
  • Audio Frequency Analysis - Analyzes audio signals by computing spectral subband centroids to characterize frequency distributions.
  • Pre-Emphasis Filters - Applies a high-pass digital filter to raw audio signals to amplify high frequencies.

Historique des stars

Graphique de l'historique des stars pour jameslyons/python_speech_featuresGraphique de l'historique des stars pour jameslyons/python_speech_features

Recherche par IA

Explorez plus de dépôts awesome

Décrivez vos besoins en langage naturel — l'IA classe des milliers de projets open source sélectionnés par pertinence.

Start searching with AI

Alternatives open source à Python Speech Features

Projets open source similaires, classés selon le nombre de fonctionnalités partagées avec Python Speech Features.
  • aubio/aubioAvatar de aubio

    aubio/aubio

    3,714Voir sur GitHub↗

    Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides a suite of tools for extracting musical features, estimating fundamental frequencies, and tracking rhythmic pulses in audio streams. The library specializes in the detection of pitch and beat, enabling the extraction of musical notes and the estimation of overall tempo. It also includes capabilities for automatic onset detection to identify the start of sonic events and the separation of audio signals into percussive transients and steady-state tonal components. The system c

    Canalysisannotationaudio
    Voir sur GitHub↗3,714
  • librosa/librosaAvatar de librosa

    librosa/librosa

    8,200Voir sur GitHub↗

    Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature extraction suite and music information retrieval tool designed to analyze the structural and sonic characteristics of audio signals. The library provides specialized capabilities for music analysis, including dynamic tempo tracking to identify rhythmic pulses and spectral feature extraction to compute harmonic spectra, chroma variants, and onset points. It also serves as a time-series audio processor for synchronizing audio streams. The system covers a broad range of audio processing

    Pythonaudiodsplibrosa
    Voir sur GitHub↗8,200
  • accord-net/frameworkAvatar de accord-net

    accord-net/framework

    4,540Voir sur GitHub↗

    This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries for numerical analysis, statistics, and mathematical optimization. It serves as a foundational toolkit for developing applications in machine learning, digital signal processing, and computer vision. The framework provides specialized toolkits for training and deploying predictive models, including neural networks, support vector machines, and decision trees. It further distinguishes itself with deep integrations for real-time visual analysis, such as object tracking and facia

    C#
    Voir sur GitHub↗4,540
  • tyiannak/pyaudioanalysisAvatar de tyiannak

    tyiannak/pyAudioAnalysis

    6,242Voir sur GitHub↗

    pyAudioAnalysis is a Python library and framework for audio signal processing and analysis. It provides tools for extracting mathematical representations of sound, such as spectrograms, and implements a system for training and evaluating machine learning models to classify audio segments based on acoustic patterns. The project includes dedicated utilities for audio segmentation, which allow for the removal of silence and the detection of specific audio events to divide recordings into meaningful sections. It also provides data visualization capabilities that use dimensionality reduction to ma

    Python
    Voir sur GitHub↗6,242
Voir les 30 alternatives à Python Speech Features→

Questions fréquentes

Que fait jameslyons/python_speech_features ?

Python speech features is a signal processing toolkit and library for extracting standard speech recognition features from raw audio signals. It provides computational capabilities to calculate mel-frequency cepstral coefficients, raw and log filterbank energies, and spectral subband centroids for automated speech recognition systems and acoustic analysis.

Quelles sont les fonctionnalités principales de jameslyons/python_speech_features ?

Les fonctionnalités principales de jameslyons/python_speech_features sont : Audio Feature Extraction, Mel-band Energy Extractions, Speech Recognition, Feature Extraction, Mel-Frequency Cepstral Coefficients, Fourier Transforms, Spectral Centroids, Windowed Segmentation.

Quelles sont les alternatives open-source à jameslyons/python_speech_features ?

Les alternatives open-source à jameslyons/python_speech_features incluent : aubio/aubio — Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides… tyiannak/pyaudioanalysis — pyAudioAnalysis is a Python library and framework for audio signal processing and analysis. It provides tools for… accord-net/framework — This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries… librosa/librosa — Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature… alphacep/vosk-api — Vosk is an offline speech-to-text engine and API that converts spoken audio into text locally on a device. It provides… allendowney/thinkdsp — ThinkDSP is a Python-based audio signal processing framework and educational resource designed for studying the…

Collections incluant Python Speech Features

Sélections manuelles où Python Speech Features apparaît.
  • Voice and audio processing