Saravanan666/pypi-org huggingface dataset:
Package: pvorcademo
Orca Text-to-Speech Engine DemoMade in Vancouver, Canada byPicovoiceOrcaOrca is an on-device text-to-speech engine producing high-quality, realistic, spoken audio with zero latency. Orca is:Private; All voice processing runs locally.Cross-Platform:Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)Android and iOSChrome, Safari, Firefox, and EdgeRaspberry Pi (5, 4, 3) and NVIDIA Jetson NanoCompatibilityPython 3.7+Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (5, 4, 3), and NVIDIA Jetson Nano.Installationpip3 install pvorcademoAccessKeyOrca requires a valid PicovoiceAccessKeyat initialization.AccessKeyacts as your credentials when using Orca
SDKs. You can get yourAccessKeyfor free. Make sure to keep yourAccessKeysecret.
Signup or Login toPicovoice Consoleto get yourAccessKey.UsageTo synthesize speech, run the following:orca_demo --access_key ${ACCESS_KEY} --text ${TEXT} --output_path ${WAV_OUTPUT_PATH}Replace${ACCESS_KEY}with yours obtained from Picovoice Console,${TEXT}with your text to be synthesized,
and${WAV_OUTPUT_PATH}with a path to a.wavfile where the generated audio will be stored as a single-channel,
16-bit PCM.wavfile.
Package: pvoutput
pvoutputPVOutput.org python API module. Works with the R2API version spec here.Get your API key fromthe account page on PVOutputExample usageHere's a quick code example:frompvoutputimportPVOutputimportjsonapikey='aaaaaabbbbbbccccccddddddeeeeeeffffffgggg'systemid=12345pvo=PVOutput(apikey=apikey,systemid=systemid)print(json.dumps(pvo.check_rate_limit(),indent=2))Will give you output like this:{
        "X-Rate-Limit-Remaining": "271",
        "X-Rate-Limit-Limit": "300",
        "X-Rate-Limit-Reset": "1570597200"
    }There are more example code snippets in theexamplesdirectory.InstallingProd-ish usagepython -m pip install pvoutputto install from pypiDev Install Thingspython-mvenvvenvsourcevenv/bin/activate
python-mpipinstall--upgradepipflit
python-mflitinstallInput validationThis is handled by thepvoutput.base.PVOutputBase.validate_datafunction.It expects the input data and a dict of configuration parameters, which are described in the table below:Field nameRequiredValid TypesDescriptiontypeYesAnyThis is a python type object to match against the field type.requiredNoboolThis defines if the field is required.descriptionNoAnyThis is currently unused, but typically holds the description from the PVOutput API Docsdonation_requiredNoboolIf set to true, and the user's not donated, it'll throw aDonationRequiredexception if the user tries to use functionality that requires them to have donated. It's a whole thing.maxlenNointMaximum length of the field. ie.if len(field) > maxlen: raise ValueErrormaxvalNointMaximum value of the field.minvalNointMinimum value of the field.additional_validatorsNoList[function]A list of functions to run against the field, which should throw exceptions if something's wrong.An example configuration"date_val": {
    "required": True,
    "description": "Date",
    "type": date,
    "donation_required": False,
    "additional_validators" : [
        validate_delete_status_date
    ]
}Contributing / Testingpylint,blackandmypyshould all pass before submitting a PR.LicenseMIT License (seeLICENSE), don't use this for anything you care about - I don't provide a warranty at all, and it'll likely steal your socks and underfeed your dog.Changelog0.0.1 Initial version0.0.2 2019-10-12 Fixed some bugs0.0.3 2019-10-13 Added PVOutput.getstatus() which returns the current status as a dict0.0.4 2019-11-05 Code cleanup using sonarqube, added an error check for registernotification0.0.5 Asyncio things0.0.6 I broke the build when uploading to pypi, fixed in 0.0.7.0.0.7 2021-12-27#117fix for getstatus issues0.0.8 2022-01-02 @cheops did great work cleaning up a lot of my mess, and testing is much better.0.0.10 2022-08-27 Added explicit timeouts to HTTP connections in the synchronous client.0.0.11 2022-08-27 Added explicit timeouts to HTTP connections in the aiohttp client.
Package: pvoutput-ocf
Download historical solar photovoltaic data fromPVOutput.org.This code is a work-in-progress.  The aim is to provide both a Python library for interacting withPVOutput.org's API, and a set of scripts for downloading lots of data :)Installation$pipinstallpvoutput-ocfRegister with PVOutput.orgYou need to get an API keyanda system ID from PVOutput.org.If you don't have a PV system, click the "energy consumption only" box
when registering on PVOutput.  If you don't include a
system ID, then you'll get a "401 Unauthorized" response from the PVOutput API.You can pass the API key and system ID into thePVOutputconstructor.
Or, create a~/.pvoutput.ymlfile which looks like:api_key:<API key from PVOutput.org>system_id:<SystemID from PVOutput.org>The default location of the.pvoutput.ymlis the user's home directory, expanded from~. This can be overridden by setting thePVOUTPUT_CONFIGenvironment variable.e.g.export PVOUTPUT_CONFIG="/my/preferred/location/.pvoutput.yml"Alternatively, you can setAPI_KEY,SYSTEM_IDandDATA_SERVICE_URL(see below) as environmental variables.API quotas and paid subscriptionsPlease seeherefor update info.FreePVOutput.org gives you 60 API requests per hour.  Per request, you can download one day of data for one PV system.  (See PVOutput's docs for more info aboutrate limits.)DonateDonating to PVOutput.orgincreases your quota for a year to 300 requests per hour.PaidTo get more historical data, you can pay $600 Australian dollars for a year's 'Live System History' subscription for a single country (more info here. Andhere's PVOutput.org's full price list).
This allows you to use theget batch statusAPI to download 900 PV-system-yearsper hour.If you have subscribed to PVOutput's data service then eitheradddata_service_urlto your configuration file (~/.pvoutput.yml) orpassdata_service_urlto thePVOutputconstructor.Thedata_service_urlshould end in.org(note this dones include the/service/r2part of the URL)
For example:data_service_url: https://pvoutput.org/Install pvoutput Python library`pip install -e git+https://github.com/openclimatefix/pvoutput.git@main#egg=pvoutput-ocfUsageSee theQuick Start notebook.Contributors ✨Thanks goes to these wonderful people (emoji key):Jack Kelly💻Sam Murphy-Sugrue💻Gabriel Tseng💻Jamie Taylor💻Peter Dudfield🚇Shanmukh Chava💻Antsthebul💻Rachit Singh🔣💻devsjc💻This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: pvplot
pvplotPackage for dynamic plotting of EPICS PVs andliteServer data objects.ExamplesSliced array plot of an EPICS PV:pvplot -s0.01 -a'E:testAPD:scope1:' 'Waveform_RBV[1:500]'Time-series plot (stripchart) of analog inputs of a LabJack U3-HV instrument, served by liteLabjack:pvplot -a'L:localhost:dev1' 'tempU3 ADC_HV[0] ADC_HV[1] ADC_HV[2] ADC_HV[3] ADC_LV'Fast correlation plot of a litePeakSimulatorpvplot -s.01 -a'L:localhost:dev1' 'x,y'Multiple docks. For example, to plot two scrolling plots in lower dock and a
correlation plot in upper dock:pvplot -a'L:localhost:dev1:' -#0'yMax yMin' -#1'yMax,yMin'To change properties of curves: right click on a plot and select 'DataSets Options'
Package: pvpn
VPN Server implemented in pure Python.(For Research Purposes Only)IntroductionAll VPN softwares are stupid, clumsy and hard to configure. So comespython-vpn.NO app install neededNO server configuration fileNO network interface addedNO iptables or “/etc” modifiedPress “RETURN” to start, “CTRL+C” to stop.QuickStart$ pip3 install pvpnSuccessfully installed pvpn-0.2.1$ pvpn -p yourpasswordServing on UDP :500 :4500...^C$ pvpn -wg 9000Serving on UDP :500 :4500...Serving on UDP :9000 (WIREGUARD)...^COpen server’s UDP port :500 :4500 to your device. In device’s system setting, add an “IPSec” (iOS) or “IPSec IKE PSK” (Android) node, write down the server address and password “yourpassword”. Connect.If you prefer wireguard VPN, specify “-wg (port)” parameter and open server’s (port) UDP port to your device. Paste the printed server public key to wireguard client settings, write down the server address:port. Connect.You should modify the default password “test” with a good one. See “pvpn -h” for more options.FeaturesClean, lightweightIKEv1, IKEv2, L2TP auto-detectionWireGuardTCP stackTCP/UDP tunnelDNS cacheProtocolsProtocol NameName in iOSName in AndroidName in MacOSName in WindowsL2TP PSK ✔L2TP“L2TP/IPSec PSK”L2TP/IPSecL2TPIKEv1 PSK ✔IPsec[1]“IPSec Xauth PSK”Cisco IPSecIPSecIKEv2 PSK ✔IKEv2[2]“IPSec IKEv2 PSK”IKEv2IKEv2WireGuard ✔WireGuard App[3][1]Do not use certificates[2]Turn off “user authentication”[3]Turn off “preshared key”ExamplesTCP TunnelIf the remote host match in file "rules.country", tunnel through http proxy.$ pvpn -r http://remote_server:port?rules.countryUDP TunnelRedirect all DNS requests to 8.8.8.8.$ pvpn -ur tunnel://8.8.8.8:53?{53}SpecificationsIPSec/ESPRFC2406IP Encapsulating Security Payload (ESP)RFC3947Negotiation of NAT-Traversal in the IKERFC3948UDP Encapsulation of IPsec ESP PacketsIKE/ISAKMPRFC2407The Internet IP Security Domain of Interpretation for ISAKMPRFC2408Internet Security Association and Key Management Protocol (ISAKMP)RFC2409The Internet Key Exchange (IKE)IANA_01Internet Key Exchange (IKE) AttributesIANA_02“Magic Numbers” for ISAKMP ProtocolDRAFT_1The ISAKMP Configuration MethodDRAFT_2Extended Authentication within IKE (XAUTH)IKEv2RFC7296Internet Key Exchange Protocol Version 2 (IKEv2)IANA_03Internet Key Exchange Version 2 (IKEv2) ParametersRFC3748Extensible Authentication Protocol (EAP)RFC5106The Extensible Authentication Protocol-Internet Key Exchange Protocol version 2 (EAP-IKEv2) MethodDiffie HellmanRFC3526More Modular Exponential (MODP) Diffie-Hellman groups for Internet Key Exchange (IKE)RFC5903Elliptic Curve Groups modulo a Prime (ECP Groups) for IKE and IKEv2RFC5114Additional Diffie-Hellman Groups for Use with IETF StandardsL2TPRFC2661Layer Two Tunneling Protocol “L2TP”RFC3193Securing L2TP using IPsecRFC1549PPP in HDLC FramingRFC1661The Point-to-Point Protocol (PPP)RFC1332The PPP Internet Protocol Control Protocol (IPCP)WireGuardRFC7748Elliptic Curves for SecurityWireGuardProtocol Specification
Package: pv.pyams
PyAMSPyAMS: Python for Analog and Mixed SignalsWhat is PyAMS?PyAMS is a software used to simplify modeling analog elements and simulate electronic circuit using Python
The objectives of PyAMS is:Drawing circuit by schematic (CAD approach: IDEPyAMS.py);Creating new PyAMS models of electrical elements by using Python language;Creating new symbols for models;Simulating the circuit in the selected mode of operation;Presenting simulation results in a dedicated waveform editor (future) and probe;Simulating the circuit by AppPyAMS commands (future);PyAMS used Python3+ and works on  Linux, Windows, and OSX.Licensed under:PyAMS is free to use. No license is necessary .NewsWhat is changed in versionsV0.0.4.3Date 02-02-2022: PyAMS Pre-alpha 0.0.4.3Update pin shape (type dot/clk)New shape: polygonElement's identifier by id.Simulator Options:Convergence:ABSTOL: the absolute current or flow tolerance.VNTOL: the absolute voltage or potontial tolerance.RELTOL: the relative voltage(potontial) and current(flow) tolerances.ITL1: the maximum number of iterations the Newton-Raphon method.Interactive:Interval: interval of simulation in miliseconds.New analog elements:Diode (Semiconductor library).Diode Zener (Semiconductor library).Diode bridge (Semiconductor library).Voltmeter (Multimeter library).Ammeter (Multimeter library).Note of installationAdd packages: PyQt5 and PyQtWebEngine by pip.install IDEPyAMS using pip:pip install IDEPyAMS.And type that command in the python shell or in source code:#for PyAMS IDE
    import IDEPyAMS;
    IDEPyAMS.exec();#for symbol editor
    import SymbolEditor;
    SymbolEditor.exec();
Package: pvqd
NoteThis Python package is still under development.This Python module provides functions to retrieve data and information easily from
Voice Foundation’s Pathological Voice Quality Database.This module currently does not retrieve the database itself on its own. User must
download and extract the files first fromhttps://prod-dcd-datasets-cache-zipfiles.s3.eu-west-1.amazonaws.com/9dz247gnyb-2.zipInstallpipinstallpvqdUsefrompvqdimportPVQD# to initialize (must call this once in every Python session)pvqd=PVQD('<path to the root directory of the extracted database>')# to get a copy of the full database with averaged CAPE-V scoresdf=pvqd.query(include_cape_v=True)# to get age, gender, and mean GRBAS grade scoresdf=pvqd.query(["Age","Gender"],include_grbas='grade')# to get a dataframe of WAV files and start and ending timestamps of all /a/ segmentdf=pvqd.get_files('/a/')# to iterate over '/a/' acoustic data of female participants along with# age and mean GRBAS scoresforid,fs,x,auxdatainpvqd.iter_data('/a/',auxdata_fields=["Age"],include_grbas=True,Gender="Female"):# run the acoustic data through your analysis function, get measurementsparams=my_analysis_function(fs,x)# log the measurements along with the age and GRBAS infomy_logger.log_outcome(id,*auxdata,*params)
Package: pvr2img
pvr2imageA Python module to easily convert Dreamcast/Naomi .PVR and .PVP files to images + palettes
Please note it requires Pillow (PIL) module installedInstallationpip3installpvr2imageExamplefiles_lst = [r"c:\temp\ALWAY.pvr",
               r"c:\temp\test\565_tw.pvr"]
out_dir = 'Extracted'
flip = ''                    
fmt = 'png'

pvr2image.decode(files_lst,fmt,out_dir,flip)```

# Image flip options:
''   = None
'v'  = vertical flip
'h'  = horizontal flip
'vh' = vertical and horizontal flip


## Credits

- Egregiousguy for YUV420 to YUV420p conversion
- Kion for VQ handling and logic
- tvspelsfreak for SR conversion info on Bump to normal map
Package: pvrecorder
PvRecorder Binding for PythonPvRecorderPvRecorder is an easy-to-use, cross-platform audio recorder designed for real-time speech audio processing. It allows developers access to an audio device's input stream, broken up into data frames of a given size.CompatibilityPython 3.5+Runs on Linux (x86_64), macOS (x86_64 and arm64), Windows (x86_64), Raspberry Pi (all variants), NVIDIA Jetson (Nano), and BeagleBone.Installationpip3 install pvrecorderUsageInitialize and begin recording:frompvrecorderimportPvRecorderrecorder=PvRecorder(frame_length=512)recorder.start()(or)Useget_available_devices()to get a list of available devices and then initialize the instance based on the index of a device:frompvrecorderimportPvRecorderdevices=PvRecorder.get_available_devices()recorder=PvRecorder(frame_length=512,device_index=0)recorder.start()Read frames of audio:whilerecorder.is_recording:frame=recorder.read()# process audio frameTo stop recording, callstop()on the instance:recorder.stop()Once you are done, free the resources acquired by PvRecorder. You do not have to callstop()beforedelete():recorder.delete()Demospvrecorderdemoprovides command-line utilities for recording audio to a file.
Package: pvrecorderdemo
PvRecorder Demo for PythonThis project contains a Python command-line demo for PvRecorder that demonstrates how to use PvRecorder to record audio to a WAV file.PvRecorderPvRecorder is an easy-to-use, cross-platform audio recorder designed for real-time speech audio processing. It allows developers access to an audio device's input stream, broken up into data frames of a given size.CompatibilityPython 3.5+Runs on Linux (x86_64), macOS (x86_64 and arm64), Windows (x86_64), Raspberry Pi (all variants), NVIDIA Jetson (Nano), and BeagleBone.Installationpip3 install pvrecorderdemoUsageIn the following instructions, we will refer to{AUDIO_DEVICE_INDEX}as the index of the audio device to use, and{OUTPUT_WAV_PATH}as the path to save the audio data inwavformat.{AUDIO_DEVICE_INDEX}defaults to -1 and{OUTPUT_WAV_PATH}can be empty if you wish to not save any data.To show the available audio devices run:pv_recorder_demo --show_audio_devicesTo run PvRecorder run:pv_recorder_demo --audio_device_index {AUDIO_DEVICE_INDEX} --output_wav_path {OUTPUT_WAV_PATH}
Package: pvrespeakerdemo
Picovoice ReSpeaker DemoMade in Vancouver, Canada byPicovoiceThis package contains a commandline demo for controlling ReSpeaker 4-mic microphone array LEDs using Picovoice.PicovoicePicovoice is an end-to-end platform for building voice products on your terms. It enables creating voice experiences
similar to Alexa and Google. But it entirely runs 100% on-device. Picovoice isPrivate:Everything is processed offline. Intrinsically HIPAA and GDPR-compliant.Reliable:Runs without needing constant connectivity.Zero Latency:Edge-first architecture eliminates unpredictable network delay.Accurate:Resilient to noise and reverberation. It outperforms cloud-based alternatives by wide margins*.Cross-Platform:Design once, deploy anywhere. Build using familiar languages and frameworks.InstallationFollow the instructions onSeeed Studioto install and set up the microphone array.Then install the demo:sudo pip3 install pvrespeakerdemoAccessKeyPicovoice requires a validAccessKeyat initialization.AccessKeys act as your credentials when using Picovoice SDKs.
You can create yourAccessKeyfor free. Make sure to keep yourAccessKeysecret.To obtain yourAccessKey:Login or Signup for a free account on thePicovoice Console.Once logged in, go to theAccessKeytabto create one or use an existingAccessKey.UsageRun the demo:picovoice_respeaker_demo --access_key ${ACCESS_KEY}SayPicovoiceThe demo outputs:[wake word]Sayturn on the lightsYou should see the lights turned on and the following message in the terminal:{
    is_understood : 'true',
    intent : 'turnLights',
    slots : {
        'state' : 'on',
    }
}The list of commands are shown on the terminal:context:
  expressions:
    turnLights:
      - "[switch, turn] $state:state (all) (the) [light, lights]"
      - "[switch, turn] (all) (the) [light, lights] $state:state"
    changeColor:
      - "[change, set, switch] (all) (the) (light, lights) (color) (to) $color:color"
  slots:
    state:
      - "off"
      - "on"
    color:
      - "blue"
      - "green"
      - "orange"
      - "pink"
      - "purple"
      - "red"
      - "white"
      - "yellow"Try changing the color by:Picovoice, set the lights to orangeTurn off the lights by:Picovoice, turn off all lights
Package: pvrhino
Rhino Speech-to-Intent EngineMade in Vancouver, Canada byPicovoiceRhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of
interest, in real-time. For example, given a spoken command:Can I have a small double-shot espresso?Rhino infers that the user would like to order a drink and emits the following inference result:{"isUnderstood":"true","intent":"orderBeverage","slots":{"beverage":"espresso","size":"small","numberOfShots":"2"}}Rhino is:using deep neural networks trained in real-world environments.compact and computationally-efficient, making it perfect for IoT.self-service. Developers and designers can train custom models usingPicovoice Console.CompatibilityPython 3.7+Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (all variants), and BeagleBone.Installationpip3 install pvrhinoAccessKeyRhino requires a valid PicovoiceAccessKeyat initialization.AccessKeyacts as your credentials when using Rhino SDKs.
You can get yourAccessKeyfor free. Make sure to keep yourAccessKeysecret.
Signup or Login toPicovoice Consoleto get yourAccessKey.UsageCreate an instance of the engine:importpvrhinoaccess_key="${ACCESS_KEY}"# AccessKey obtained from Picovoice Console (https://console.picovoice.ai/)handle=pvrhino.create(access_key=access_key,context_path='/absolute/path/to/context')Wherecontext_pathis the absolute path to Speech-to-Intent context created either usingPicovoice Consoleor one of the default contexts available on Rhino's GitHub repository.The sensitivity of the engine can be tuned using thesensitivityparameter. It is a floating-point number within
[0, 1]. A higher sensitivity value results in fewer misses at the cost of (potentially) increasing the erroneous
inference rate.importpvrhinoaccess_key="${ACCESS_KEY}"# AccessKey obtained from Picovoice Console (https://console.picovoice.ai/)handle=pvrhino.create(access_key=access_key,context_path='/absolute/path/to/context',sensitivity=0.25)When initialized, the valid sample rate is given byhandle.sample_rate. Expected frame length (number of audio samples
in an input array) ishandle.frame_length. The engine accepts 16-bit linearly-encoded PCM and operates on
single-channel audio.defget_next_audio_frame():passwhileTrue:is_finalized=rhino.process(get_next_audio_frame())ifis_finalized:inference=rhino.get_inference()ifnotinference.is_understood:# add code to handle unsupported commandspasselse:intent=inference.intentslots=inference.slots# add code to take action based on inferred intent and slot valuesWhen done resources have to be released explicitly:handle.delete()Non-English ContextsIn order to run inference on non-English contexts you need to use the corresponding model file. The model files for all supported languages are availablehere.Demospvrhinodemoprovides command-line utilities for processing real-time
audio (i.e. microphone) and files using Rhino.
Package: pvrhinodemo
Rhino Speech-to-Intent Engine DemosMade in Vancouver, Canada byPicovoiceThis package contains demos and commandline utilities for processing real-time audio (i.e. microphone) and audio files
using Rhino Speech-to-Intent engine.RhinoRhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of
interest, in real-time. For example, given a spoken commandCan I have a small double-shot espresso?Rhino infers that the user and emits the following inference result:{"isUnderstood":"true","intent":"orderBeverage","slots":{"beverage":"espresso","size":"small","numberOfShots":"2"}}Rhino is:using deep neural networks trained in real-world environments.compact and computationally-efficient. It is perfect for IoT.self-service. Developers can train custom models usingPicovoice Console.CompatibilityPython 3.7+Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (all variants), NVIDIA Jetson Nano and BeagleBone.Installationsudo pip3 install pvrhinodemoAccessKeyRhino requires a valid PicovoiceAccessKeyat initialization.AccessKeyacts as your credentials when using Rhino SDKs.
You can get yourAccessKeyfor free. Make sure to keep yourAccessKeysecret.
Signup or Login toPicovoice Consoleto get yourAccessKey.UsageFile DemoIt allows testing Rhino on a corpus of audio files. The demo is mainly useful for quantitative performance
benchmarking. It accepts 16kHz audio files. Rhino processes a single-channel audio stream if a stereo file is
provided it only processes the first (left) channel. Note that only the relevant spoken command should be present in the
file and no other speech. There also needs to be at least one second of silence at the end of the file.rhino_demo_file --wav_path ${AUDIO_PATH} --access_key ${ACCESS_KEY} --context_path ${CONTEXT_PATH}Microphone DemoIt opens an audio stream from a microphone and performs inference in spoken commands:rhino_demo_mic --access_key ${ACCESS_KEY} --context_path ${CONTEXT_PATH}It is possible that the default audio input device recognized by the demo is not the one being used. There are a couple
of debugging facilities baked into the demo application to solve this. First, type the following into the console:rhino_demo_mic --show_audio_devicesIt provides information about various audio input devices on the box. On a Linux box, this is the console outputindex: 0, device name: USB Audio Device
index: 1, device name: MacBook Air MicrophoneYou can use the device index to specify which microphone to use for the demo. For instance, if you want to use the USB Audio Device
in the above example, you can invoke the demo application as below:rhino_demo_mic --access_key ${ACCESS_KEY} --context_path ${CONTEXT_PATH} --audio_device_index 0If a problem occurs, we suggest storing the recorded audio into a file for inspection. This can be achieved by:rhino_demo_mic --access_key ${ACCESS_KEY} --context_path ${CONTEXT_PATH} --audio_device_index 0 --output_path ~/test.wav