Saravanan666/pypi-org huggingface dataset:
Package: audiorepr
audioreprA python package to represent data using musical notes.Installationpip install audioreprExamplesDemo inexamples/covid19.py.importpandasaspdfromaudioreprimportaudiolizeecdc="https://gist.githubusercontent.com/emptymalei/90869e811b4aa118a7d28a5944587a64/raw/1534670c8a3859ab3a6ae8e9ead6795248a3e664/ecdc%2520covid%252019%2520data"df=pd.read_csv(ecdc)audiolize.audiolizer(df,target="ecdc-covid19-by-date.midi",pitch_columns=["DE","AT","FR"])By default, we use a min-max mapper to map the data onto midi notes 16 to 96. You can easily write your own mapper or simply map your own data on to the range [0, 126].The specified pandas dataframe columns will be mapped onto different tracks.audiolize.audiolizeralso accepts numpy array or list as data input.Play the output midi file using the player of your choice.timidity(Mac,Win,Linux): a midi play in your terminal.GarageBand(Mac): free software by Apple. GarageBand allows you to change tune the audio by changing the volumes, instruments, tempo, etc.Documentation[WIP]DevelopmentCreate a new environment:conda create -n audiorepr python=3.7 pipInstal requirements:pip install -r requirementsGenerate DocumentationThe documentation is generated through sphinx.cd docsmake htmlThe generated documentation is located insidebuild/html.To update the documentation, update the.rstfiles in thesourcefolder.PublishingPublishing toPYPI service:Runpython setup.py sdist bdist_wheelTest upload:python -m twine upload --repository testpypi dist/*Upload:python -m twine upload dist/*
Package: audioscrape
AudioscrapeScrape audio from various websites with a simple command-line interface.UsageFirst make sure Python is installed, then run:pipinstallaudioscrapeThen you can use the program as:audioscrape"acoustic guitar"Seeaudioscrape --helpfor more details.Python APIYou can also use the scraper directly in Python, as:importaudioscrapeaudioscrape.download(query="Cerulean Crayons",include=["guitar"],exclude=["remix"],quiet=True,)DevelopFirst clone the repo and set it as working directory. Then install the package in development mode (preferably within its own virtual environment):pipinstall-e.[tests]If you havedirenvinstalled, you can rundirenv allowto automatically create and activate a Python virtual environment when you enter the directory.TestpytestLintpre-commitrun--all-filesOrpre-commit installto run automatically ongit commit.
Package: audioset-download
AudioSet DownloadThis repository contains code for downloading theAudioSetdataset.
The code is provided as-is, and is not officially supported by Google.RequirementsPython 3.9 (it may work with other versions, but it has not been tested)Installation# Install ffmpegsudoaptinstallffmpeg# Install audioset-downloadpipinstallaudioset-downloadUsagefromaudioset_downloadimportDownloaderd=Downloader(root_path='test',labels=None,n_jobs=2,download_type='unbalanced_train',copy_and_replicate=False)d.download(format='vorbis')
Package: audio-silence-marks
Create silence marks for your audio filesCreates a list of "silences" timecodes in audio files usingFFmpegand its filtersilencedetect.Currently, onlyAudipoplayer marks format is supported.PrerequisitesPython 3.8+FFmpegLinux (haven't tested on Windows/Mac yet)Installation$ pip install audio_silence_marksUsageRun the tool against one file or a directory tree:$ audio_silence_marks . file.mp3 > marks.audipomark
$ audio_silence_marks . '**/*.mp3' > marks.audipomarkThen upload this file to your phone's directoryInteral Storage/Audipo/Mark, e.g.:$ adb push marks.audipomark /storage/emulated/0/Audipo/Mark/Open your Audipo player, go toMenu > Preferencesand click onImport all marksitem.
Restart the player.ResultExample:Unit 23Unit 24Processing audiobooksThe script accepts two parameters which highly affect the output, i.e. the amount and the positions of the marks.
They are:--noise,-n- noise tolerance in decibels (negated for convenience).Acts like a reverse noise gate, passing through parts with the volume below defined. The default value is50(which makes-50dB).--duration,-d- duration of silence in milliseconds.Sets the minimum duration of silence. The default value is1000(ms).Thus, even a book with some background music which level is less than of the speech, can be successfully marked by--noiseparameter tuning.An example profile for a regular book:audio_silence_marks -d 400 -n 30 . book.mp3 > marks.audipomarkThis sets-30dBnoise level and400millisecond minimum silence duration.Docs$ audio_silence_marks --help

Usage: audio_silence_marks [OPTIONS] PATH GLOB

  Processes audio files using FFmpeg filter silencedetect and outputs Audipo
  markers JSON with the list of spots placed in the middle of silence
  intervals.

  More info on using GLOBS: https://docs.python.org/3.8/library/glob.html

Arguments:
  PATH  is a path to files. E.g: "."  [required]
  GLOB  argument is a pattern for selecting files. E.g.: '**/*.mp3'
        [required]


Options:
  -t, --target [audipo]           Target format for marks.  [default: audipo]
  -n, --noise INTEGER             Maximum volume of the noise treated as
                                  silence in -dB  [default: 50]

  -d, --duration INTEGER          Minimum length of the silent interval in
                                  milliseconds [default: 1000]

  -l, --list                      Simply lists matched files. Useful for GLOB
                                  debugging.  [default: False]

  --install-completion [bash|zsh|fish|powershell|pwsh]
                                  Install completion for the specified shell.
  --show-completion [bash|zsh|fish|powershell|pwsh]
                                  Show completion for the specified shell, to
                                  copy it or customize the installation.

  --help                          Show this message and exit.
Package: audio-sleuth
Audio SleuthA torch based open-source framework for detecting audio generated from generative systems. The overarching goal of this repository is to be a toolbox for datasets, augmentations, and pretrained baseline models to assist researchers in the task of audio deepfake detection.InstallTo install, simply use pip:pip install audio-sleuthUsageThe goal of this package is to contain augmentations, models, and losses all as atorch.nn.Moduleclass. Each augmentation contains an internalLabelAlignmentsuch that you can implement various time-frequency transformations to automatically translate the sample-wise labels as well.Here is an example of how to chain together augmentations on the Half Truth Dataset.fromaudio_sleuth.augmentationsimportResample,LFCC,Augmentationsfromaudio_sleuth.data.datasetsimportHalfTruthDataset# Augmentation chaintransform=Augmentations([Resample(input_sr=48000,new_sr=16000,return_original_sr=False),# Downsample blockLFCC(fs=16000,n_fft=512,hop_size=128,win_size=128,n_filters=128,n_lfcc=40# LFCC augmentation)])# Returns torch Dataset that can be fed into DataLoaderdataset=HalfTruthDataset(path_to_txt,# Initialize to your txt file of filepaths and labels from datasetfs=16000,transform=transform)
Package: audio-slice
Audio SliceDescriptionThis tool slices an MP3 file in to a specified number of pieces. Using this
command line tool, you can extract multiple audio files from one master file.Current Development StatusThis tool is still in its early stages and can only be described as "quick and
dirty". You should be comfortable with everything that comes along with that
descriptor.Usage DependenciesHere are the required dependencies to use this tool:FFmpegPython 2.7+InstallationThe easiest way to install this tool is to use PIP. No other method of
installation is officially supported at this time.PIP (OS/X Installation Instructions)Installing Audio Slice can be achieved by running the following command once
you have PIP installed:pipinstall--useraudio-sliceIf you're upgrading to a new version of Audio Slice, you simply use:pipinstall--useraudio-slice--upgradeUsageRecommended usageIf you're going to use this tool, the recommended usage is to do any file-renaming you have to do first, and then move on to the slicing.File renamingYou should rename all of the files BEFORE performing any slice operations.
In order to rename the files, it only works by navigating directly to the
directory containing all of the files. Once you've navigated there, then you can
type the following command:slice.renameThis will rename all of the files in the directory to just their participant IDs.
During the slicing process, the tags will be added on to the end of the slices.Slicingslice--piece<start_in_seconds><end_in_seconds>--tags<tag>,<tag>,<tag><filename>Example:slice--piece24.334.1--piece35.341.2--tagspig,booknever_gonna_give_you_up.mp3A few things to note about using the tool:You can create as many slices of the audio as you need to; even if they overlap. You simply need to add another--piece <start> <end>option to the command line.The tool will place the output files in the same directory as the input file.You specify the start and end of a slice in seconds that can include greater precision. (Ex: 74.3)Currently, this only works with MP3s.ProblemsThe following are known solutions to problems that have been raised:slice command not foundIf you're having a problem executing theslicecommand at the command line,
your Python binary folder may not be in your PATH. If you need to add the
Python binary directory to your PATH, you can do the following (MacOS only):echo'export PATH="$PATH:~/Library/Python/2.7/bin"'>>~/.bash_profilesource~/.bash_profile
Package: audio-snippets
audio-snippetsInstallpipinstallaudio-snippetsUsageI suggest you use jupyter notebooks to take full advantage of all functionsLoad Audiofromaudio_snippetsimportSounds=Sound.from_path('/path/to/audio/file.mp3')Dataprint(s.audio)# just the numpy array :Dprint(s.Fs)# sampling frequencyPlay its.play()s.play(x=5)# play the audio in 5x speedSize of audiolen(s)# Number of sampless.size# Number of seconds of audios.formatted_size# length of the audio in seconds/minutes/hours# E.g.  # 5.323 seconds ; 6.43 minutes ; 1.53 hoursSlice the audiot=s[3:5]# Slices the audio from 3 to 5 secondst.play()t=s[:5]# Slice first 5 secondst=s[5:]# Slice from 5 seconds onwardt=s[::2]# select every second sample (speeds the audio by 2x)Plot the waveforms.plot()# interactive plotlys.plot(slice(5,25))# plot a slice of the waveform
Package: audio-splitter
Audio File Splitteraudio_splitter/main.pyis a command-line tool for splitting audio files into equally-sized chunks or based on silence. This Python script uses thepydublibrary for handling various audio formats.Why does this exist?As someone who enjoys to listen to spoken word every night, I often listen to podcasts on my old MP3 player before going to sleep. However, I found myself growing bored of listening to the same first 5 minutes of each episode every night. To mix things up and always have something new to listen to, I created this script to break down podcast episodes into smaller chunks. Now I can jump around different parts of the episodes and enjoy a fresh listening experience each time.UsageTo use the script, follow these steps:pythonaudio_splitter/main.pyinput_fileoutput_dir[--chunk_lengthCHUNK_LENGTH][--output_formatOUTPUT_FORMAT][--silence_based]Replace input_file with the path to your audio file and output_dir with the path to the output directory where you want to save the chunks.Options--chunk_lengthCHUNK_LENGTH:Lengthofeachchunkinmilliseconds(default:300000ms,or5minutes).Ignoredif--silence_basedisset.
--output_formatOUTPUT_FORMAT:Outputformatfortheaudiochunks(default:wav).Supportedformatsincludewav,mp3,andogg.
--silence_based:Splittheaudiobasedonsilenceinsteadoffixed-sizechunks.Ifset,--chunk_lengthisignoredandthescriptensuresthatthegeneratedchunksareatleastthespecifiedlength.ExamplesSplit an audio file into 5-minute (default) chunks:pythonaudio_splitter/main.pyinput_file.mp3output_dirSplit an audio file into 10-minute chunks and save them in the MP3 format:pythonaudio_splitter/main.pyinput_file.mp3output_dir--chunk_length600000--output_formatmp3Split an audio file based on silence, ensuring that the chunks are at least 5 minutes long:pythonaudio_splitter/main.pyinput_file.mp3output_dir--silence_basedSplit an audio file based on silence, ensuring that the chunks are at least 10 minutes long:pythonaudio_splitter/main.pyinput_file.mp3output_dir--chunk_length600000--silence_based
Package: audiosr
AudioSR: Versatile Audio Super-resolution at ScalePass your audio in, AudioSR will make it high fidelity!Work on all types of audio (e.g., music, speech, dog, raining, ...) & all sampling rates.Share your thoughts/samples/issues in our discord channel:https://discord.gg/HWeBsJryafChange Log2023-09-24: Add replicate demo (@nateraw); Fix error on windows, librosa warning etc (@ORI-Muchim).2023-09-16: Fix DC shift issue. Fix duration padding bug. Update default DDIM steps to 50.Commandline UsageInstallation# Optionalcondacreate-naudiosrpython=3.9;condaactivateaudiosr# Install AudioLDMpip3installaudiosr==0.0.7UsageProcess a list of files. The result will be saved at ./output by default.audiosr-ilbatch.lstProcess a single audio file.audiosr-iexample/music.wavFull usage instruction>audiosr-h

>usage:audiosr[-h]-iINPUT_AUDIO_FILE[-ilINPUT_FILE_LIST][-sSAVE_PATH][--model_name{basic,speech}][-dDEVICE][--ddim_stepsDDIM_STEPS][-gsGUIDANCE_SCALE][--seedSEED]optionalarguments:-h,--helpshowthishelpmessageandexit-iINPUT_AUDIO_FILE,--input_audio_fileINPUT_AUDIO_FILEInputaudiofileforaudiosuperresolution-ilINPUT_FILE_LIST,--input_file_listINPUT_FILE_LISTAfilethatcontainsallaudiofilesthatneedtoperformaudiosuperresolution-sSAVE_PATH,--save_pathSAVE_PATHThepathtosavemodeloutput--model_name{basic,speech}Thecheckpointyougonnause-dDEVICE,--deviceDEVICEThedeviceforcomputation.Ifnotspecified,thescriptwillautomaticallychoosethedevicebasedonyourenvironment.--ddim_stepsDDIM_STEPSThesamplingstepforDDIM-gsGUIDANCE_SCALE,--guidance_scaleGUIDANCE_SCALEGuidancescale(Large=>betterqualityandrelavancytotext;Small=>betterdiversity)--seedSEEDChangethisvalue(anyintegernumber)willleadtoadifferentgenerationresult.--suffixSUFFIXSuffixfortheoutputfileTODOAdd gradio demo.Optimize the inference speed.Cite our workIf you find this repo useful, please consider citing:@article{liu2023audiosr,title={{AudioSR}: Versatile Audio Super-resolution at Scale},author={Liu, Haohe and Chen, Ke and Tian, Qiao and Wang, Wenwu and Plumbley, Mark D},journal={arXiv preprint arXiv:2309.07314},year={2023}}
Package: audiostack
audiostack SDKaudiostack is the officialaudiostackPython 3 SDK. This SDK provides easy access to the api.audio API for applications written in python.Maintainershttps://github.com/Sjhunt93LicenseThis project is licensed under the terms of the MIT license.🧐 AboutThis repository is actively maintained byAudiostack. For examples, recipes and api reference see theapi.audio docs. Feel free to get in touch with any questions or feedback!:book:  ChangelogYou can viewhereour updated Changelog.:speedboat:  QuickstartsGet started with ourquickstart recipes.🏁 Getting StartedInstallationYou don't need this source code unless you want to modify it. If you want to use the package, just run:pipinstallaudiostack-U#orpip3installaudiostack-UPrerequisitesPython 3.6+🚀 Hello WorldCreate a filehello.pytouchhello.pyAuthenticationThis library needs to be configured with your account's api-key which is available in yourapi.audio Console. Import the audiostack package and setaudiostack.api_keywith the api-key you got from the console:importaudiostackaudiostack.api_key="your-key"Create Text to audio in 4 stepsLet's create our first audio asset.✍️ Create a new script, ourscriptTextwill be the text that is later synthesized.script=audiostack.Content.Script.create(scriptText="hello world")print(script.message,script.scriptId)🎤 Render the scriptText that was created in the previous step. Lets use voice Aria. Lets download our tts file also.tts=audiostack.Speech.TTS.create(scriptItem=script,voice="Aria")print(tts)tts.download(autoName=True)🎧 Now let's mix the speech we just created with a sound template.mix=audiostack.Production.Mix.create(speechItem=tts,soundTemplate="jakarta")print(mix)Lets convert out produced mix into a mp3 and download it.enc=audiostack.Delivery.Encoder.encode_mix(productionItem=mix,preset="mp3_low")enc.download()Easy right? 🔮 This is the finalhello.pyfile.importaudiostackaudiostack.api_key="your-key"script=audiostack.Content.Script.create(scriptText="hello world")print(script.message,script.scriptId)tts=audiostack.Speech.TTS.create(scriptItem=script,voice="Aria")print(tts)tts.download(autoName=True)mix=audiostack.Production.Mix.create(speechItem=tts,soundTemplate="jakarta")print(mix)enc=audiostack.Delivery.Encoder.encode_mix(productionItem=mix,preset="mp3_low")enc.download()Now let's run the code:pythonhello.py#orpython3hello.pyOnce this has completed, find the downloaded audio asset and play it! :sound: :sound: :sound:ImportimportaudiostackAuthenticationThe library needs to be configured with your account's secret key which is available in yourAflorithmic Dashboard. Setaudiostack.api_keywith the api-key you got from the dashboard:audiostack.api_key="your-key"Authentication with environment variable (recommended)You can also authenticate usingaudiostack_keyenvironment variable and the audiostack SDK will automatically use it. To setup, open the terminal and type:exportaudiostack_key=<your-key>If you provide both an environment variable andaudiostack.api_keyauthentication value, theaudiostack.api_keyvalue will be used instead.
Package: audiostems
AudiostemsAudio STEM Separation powered bySpleeterDownload Youtube Audio to WAV and Separate StemsWhat is a stem?Stems are the different components that make up a music, in most cases you have vocals, drums, bass, and other instrumentation. According to the current scientific status, there will never be an algorithm that restores the exact master tracks before mixing, but with machine learning some people have developed some methods for estimation. There are different approaches largely depending on how much spare time you have on your hands.Method: Train your own neural network & Build your own database: Not possible unless you have a lot of experience and a lot of work. (Use work synonomous for time because time and space are connected)Method: Train your own network with someone else's dataset, possible good results require a lot of experience + workMethod: Use someone else's pretrained network, that is what the Audiostems Project is, It depends on the Spleeter Network developed by a team at deezer.comMethod: Use someone else's shitty website that requires you to login to process a reasonable amount of data.As you can see the goal of this Project is to provide creative minds with the right tools. This is more like a toolbox.
Package: audiosync
Aboutaudiosync syncs digital audio workstation projects between computers.PrerequisitesPythonhttp://www.python.orgInstallationUnzip the file, then at the command line runpython setup.py installDocumentationTo read the API documentation, open a shell / DOS window, navigate to
the audiosync directory, and runpydoc audiosyncYou can create a HTML version usingpydoc -w audiosyncLicenseaudiosync is licensed under the GPL. See the file COPYING for details.AuthorFlorian Berger
Package: audiotagger
audiotaggerCross-platform metadata editor for audio files.Dependenciesmutagen: Developed on 1.41.1 and
higher.  May work for earlier versions.pandas: Developed on 0.20.3 and
higher.  May work for earlier versions.openpyxl: Developed on 2.5.11
and higher.  May work for earlier versions.xlrd: Developed on 1.1.0 and higher.  May work for earlier versions.SetupAll commands are executed fromaudiotagger.audiotagger.api.main.  First run
the following to generate a configuration file.--generate-configThis generates a configuration file in the~/.audiotaggerdirectory.ExampleThis extracts the metadata from a single audio file.  Passing-xwrites
the output to an Excel (.xlsx) file.-s /path/to/file -xSimilar to the above, you can extract metadata from several files by
passing in a directory.-s /path/to/album -xTo tag audio file(s) using a metadata input file, change the source to
a metadata input file and pass the-toption.-s /path/to/metadata_input_file.xlsx -t
Package: audiotimer
Audio timerGithub:https://github.com/ARanch/audiotimerThis small program starts listening for an audio input on the system microphone. When a set audio level threshold is reached, a timer is started. When the audio level is reduced below the threshold, the timer is stopped after a short countdown, and the timespan is logged.python -m pip install audiotimerinstall requirements:pip install -r requirements.txtrun using:python audiotimersee -h flag for run-time options.Use caseThe program is intended to be used as a way of testing the battery life of battery powered loudspeakers. Set the speaker to play a pink noise at a certain level, and leave a laptop with the speaker to listen for when it dies out.
Package: audio_title_tag
说明批量设置文件夹内的mp3、flac音频文件元数据标签的标题为当前文件名称如文件名称为 胖虎演唱.mp3 那么音频文件元数据标签的标题会设置为 胖虎演唱用法1终端进入项目位置安装环境pip install -r requirements.txt终端输入python audio_title_tag.py <文件夹路径>例子cdD:\audio_title_tagpipinstall-rrequirements.txt# 安装环境只需要执行一次pythonaudio_title_tag.pyD:\audio用法2pip install audio_title_tagimportaudio_title_tagaudio_title_tag.update_audio_metadata('<文件夹路径>')
Package: audio-to-animation-video
Audio To Animation VideoInstallationpip install audio-to-animation-videoGet startedHow to multiply one number by another with this lib:# Example usageframe_sz=(720,500)images_directory='image/girl1'image_filename='girl'# file should be girl_A.png or jpgaudio_file="audio/audio1.mp3"output_video_path='video.mp4'output_path='video_with_audio3.mp4'background=(255,255,255)# "image/bg/bg1.jpg" #(255, 255, 255)generator=AudioLipSyncVideo(images_directory,image_filename,audio_file,output_video_path,output_path,frame_sz,background)generator.generate_video()
Package: audio-to-midi
audio-to-midiaudio-to-miditakes in a sound file and converts it to a multichannel MIDI file. It accomplishes this by performing FFT's on all channels of the audio data at user specified time steps. It then separates the resulting frequency analysis into equivalence classes which correspond to the twelve tone scale; the volume of each class being the average volume of its constituent frequencies. It then formats this data for MIDI and writes it out to a user specified file. It has the ability to convert whichever audio file formats are supported by thesoundfilemodule. libsndfile must be installed before runningaudio-to-midiThis is an example of a conversion using a time window of 5ms and an activation level of 0.Installation> python3 ./setup.py installUsage>audio-to-midi--help
usage:audio-to-midi[-h][--outputOUTPUT][--time-windowTIME_WINDOW][--activation-levelACTIVATION_LEVEL][--condense][--condense-max][--single-note][--note-countNOTE_COUNT][--bpmBPM][--transposeTRANSPOSE][--keyKEY[KEY...]][--no-progress]infile

positionalarguments:infileThesoundfiletoprocess.

optionalarguments:-h,--helpshowthishelpmessageandexit--outputOUTPUT,-oOUTPUTTheMIDIfiletooutput.Default:<infile>.mid--time-windowTIME_WINDOW,-tTIME_WINDOWThetimespanoverwhichtocomputetheindividualFFTsinmilliseconds.--activation-levelACTIVATION_LEVEL,-aACTIVATION_LEVELTheamplitudethresholdfornotestobeaddedtotheMIDIfile.Mustbebetween0and1.--condense,-cCombinecontiguousnotesattheiraverageamplitude.--condense-max,-mWritethemaximumvelocityforacondensednotesegmentratherthantherollingaverage.--single-note,-sOnlyaddtheloudestnotetotheMIDIfileforagiventimewindow.--note-countNOTE_COUNT,-CNOTE_COUNTOnlyaddtheloudestnnotestotheMIDIfileforagiventimewindow.--bpmBPM,-bBPMBeatsperminute.Defaults:60--transposeTRANSPOSE,-TTRANSPOSETransposetheMIDIpitchesbyaconstantoffset.--keyKEY[KEY...],-kKEY[KEY...]Maptoapitchset.--no-progress,-nDon'tprinttheprogressbar.Example>$audio-to-midi./this_is_a_test.wav-b120-t30./this_is_a_test.wav
samplerate:44100Hz
channels:1duration:2.000s
format:WAV(Microsoft)[WAV]subtype:Signed16bitPCM[PCM_16]window:5.0ms
frequencies:min=200.0Hz,max=20000Hz100%(401of401)|##############################################################| Elapsed Time: 0:00:00 Time:  0:00:00>ls./*.mid
./this_is_a_test.wav.mid