{"id":18682653,"url":"https://github.com/linto-ai/sfeatpy","last_synced_at":"2025-11-07T17:30:33.059Z","repository":{"id":57466058,"uuid":"339407399","full_name":"linto-ai/sfeatpy","owner":"linto-ai","description":"Library to extract MFCC features from audio signal","archived":false,"fork":false,"pushed_at":"2021-02-16T14:36:23.000Z","size":19,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-01-28T21:17:03.118Z","etag":null,"topics":["feature-extraction","mfcc","mfcc-features","python3","speech-processing"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"agpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/linto-ai.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-02-16T13:28:50.000Z","updated_at":"2024-06-19T07:16:57.000Z","dependencies_parsed_at":"2022-08-31T03:23:11.064Z","dependency_job_id":null,"html_url":"https://github.com/linto-ai/sfeatpy","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linto-ai%2Fsfeatpy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linto-ai%2Fsfeatpy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linto-ai%2Fsfeatpy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linto-ai%2Fsfeatpy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/linto-ai","download_url":"https://codeload.github.com/linto-ai/sfeatpy/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239533418,"owners_count":19654677,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["feature-extraction","mfcc","mfcc-features","python3","speech-processing"],"created_at":"2024-11-07T10:12:28.651Z","updated_at":"2025-11-07T17:30:33.006Z","avatar_url":"https://github.com/linto-ai.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SFeatPy\n![version](https://img.shields.io/github/manifest-json/v/linto-ai/sfeatpy)   [![pypi version](https://img.shields.io/pypi/v/sfeatpy)](https://pypi.org/project/sfeatpy/)\n## Introduction\n\nPython library to extract MFCC parameters.\n\n## Installation\n\n### pypi\n\n```bash\npip install sfeatpy\n```\n\n### From source\n\n```bash\ngit clone https://github.com/linto-ai/sfeatpy.git\ncd sfeatpy\n./setup.py install\n```\n\n## Usage\n\n```python\nimport sfeatpy\nimport numpy as np\n\nrd_signal = np.random.random(16000)\n\nres = sfeatpy.mfcc(rd_signal,           # audio signal\n                   sample_rate,         # sample_rate -- Audio sampling rate (default 16000)  \n                   window_length,       # window_length -- window size in sample (default 1024)  \n                   window_stride,       # window_stride -- window stride in sample (default 512)  \n                   fft_size,            # fft_size -- fft number of points (default 1024) \n                   min_freq,            # min_freq -- minimum frequency in hertz (default 20) \n                   max_freq,            # max_freq -- maximum frequency in hertz (default 7000) \n                   num_filter,          # num_filter -- number of MEL bins (default 40) \n                   num_coef,            # num_coef -- number of output coeficients (default 20) \n                   windowFun,           # windowFun -- window function: 0- None | 1- hamming (default 0) \n                   preEmp,              # preEmp -- preEmphasis factor ignored on None (default 0.97) \n                   keep_first_value     # keep_first_value -- if False discard first MFCC value (default False)\n                   )\nres.shape\n\u003e (30,20)\n\n```\n\n## Limitations\n\n* Values are not checked to keep the processing efficient.\n* Works only on Mono-channel signal\n\n## Licence\nThis project is under aGPLv3 licence, feel free to use and modify the code under those terms.\nSee LICENCE\n\n## Used libraries\n\n* [Numpy](http://www.numpy.org/)\n* [Scipy](https://github.com/tensorflow/tensorflow)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinto-ai%2Fsfeatpy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flinto-ai%2Fsfeatpy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinto-ai%2Fsfeatpy/lists"}