Sound on Raspberry Pi: Separate speaker and microphone

While seemingly simple, getting a USB microphone + a speaker connected to 3.5mm audio jack working AT THE SAME TIME can be very challenging.

Some of the common errors seen when trying to record and play audio

  • arecord: main:788: audio open error: No such file or directory
  • aplay: set_params:1305: Channels count non available

Find out device IDs

Speaker device

To see which devices are available to use as a speaker, use the following command

pi@raspberrypi:~ $ aplay -l
**** List of PLAYBACK Hardware Devices ****
card 0: ALSA [bcm2835 ALSA], device 0: bcm2835 ALSA [bcm2835 ALSA]
  Subdevices: 7/7
  Subdevice #0: subdevice #0
  Subdevice #1: subdevice #1
  Subdevice #2: subdevice #2
  Subdevice #3: subdevice #3
  Subdevice #4: subdevice #4
  Subdevice #5: subdevice #5
  Subdevice #6: subdevice #6
card 0: ALSA [bcm2835 ALSA], device 1: bcm2835 IEC958/HDMI [bcm2835 IEC958/HDMI]
  Subdevices: 1/1
  Subdevice #0: subdevice #0
card 1: Microphone [USB Microphone], device 0: USB Audio [USB Audio]
  Subdevices: 1/1
  Subdevice #0: subdevice #0

Based on the above output we have three devices:

  • The onboard 3.5mm plug listed as BCM2835 ALSA: Card 0, Device 0 (“hw:0,0”)
  • The onboard HDMI connection listed as bcm2835 IEC958/HDMI: Card 0, Device 1 (“hw:0,1”)
  • The USB microphone listed as USB Audio: : Card 1, Device 0 (“hw:1,0”)

In this example we want to use the 3.5mm audio jack, so we’ll use Card 0, Device 0 as the way to locate our speaker device. The USB microphone doesn’t have audio output and is not valid as a speaker setting. It is listed however, which can cause confusion.

Microphone device

To see which devices are available to use as a microphone, use the following command

pi@raspberrypi:~ $ arecord -l
**** List of CAPTURE Hardware Devices ****
card 1: Microphone [USB Microphone], device 0: USB Audio [USB Audio]
  Subdevices: 1/1
  Subdevice #0: subdevice #0

We only have one device and that’s the USB microphone listed as Card 1 and Device 0 (“hw:1,0”).

Configuring the audio settings

To set the audio settings, create or modify the .asoundrc file in the users home directory as follows. That would be /home/pi/.asoundrc for the default user.

pi@raspberrypi:~ $ cat .asoundrc
pcm.!default {
  type asym
  capture.pcm "mic"
  playback.pcm "speaker"

pcm.mic {
  type plug
  slave {
    pcm "hw:1,0"

pcm.speaker {
  type plug
  slave {
    pcm "hw:0,0"

Logging out / in, rebooting or reloading the audio service would apply the settings.

To apply the settings system-wide, copy the .asoundrc file to /etc/asound.conf

Test the new settings

To test recording audio, use arecord without specifying the device to record from (if our settings are correct, the default device would already be configured and picked up by arecord):

arecord -f S16_LE -r 48000 test.wav

To play the recorded sound use aplay

aplay test.wav

Sample rate

If things still don’t work, consider checking the sampling rate of the microphone. I had bought a new mic for use with AWS Lex and Alexa but it wouldn’t work. The sampling rate required was 16000 and the mic didn’t support it.

It turns out an old PlayStation3 camera has a 16000 sample rate. Checking rate by the following:

cat /proc/asound/card1/stream0 | egrep -i rate<br>
    Rates: 16000

EdgeX Foundry version 1.0 is now available

The Open Source IoT solution called EdgeX Foundry has just had it’s first Long-Term Support (LTS) release. This is a big deal and a real milestone since it’s finally out of 0.x versions and into the first, big 1.x release. After a journey of over 2 years it’s finally ready for broad adoption. EdgeX Foundry is an official Linux Foundation project and part of LF Edge.

Why is EdgeX Foundry so relevant?

Data ingestion

  • It is a native speaker of the protocols and data formats of a myriad edge devices
  • Without the need for agents, it ingests data from most edge devices and sensors
  • It converts the data to XML or JSON for easy processing
  • It streams the data in real-time to internal or external cloud and big-data platforms for visualization and processing

Control and automation

  • It supports the native commands of edge devices and can change camera angles, fan speeds, etc.
  • It has rules that can act on input and trigger commands for instant action and automation


  • EdgeX Foundry is cloud-native
  • It’s open source and can be downloaded by anyone free of charge
  • It’s made up of microservices running in docker containers
  • It’s modular, flexible and can be integrated into other IoT management systems

How does it fit in with the rest of the IoT world?

While the Internet of Things is fairly new and very much a buzzword, the concept of connected devices runs back much longer through the Machine 2 Machine era.

Oftentimes these solutions are vendor-specific, siloed off and lack any unified layer for insight, control and management. EdgeX Foundry bridges not only the old M2M with the new IoT solutions but also connects the Edge to the core DC to the Cloud. It’s the glue that holds the world of IoT together.

It can favorably be used both stand-alone, as a part of a larger IoT solution (containers can easily be integrated as they contain individual services) or together with a commercial IoT solution such as VMware Pulse IoT Center 2.0.

How to get started

Many resources are available for those looking to get started with EdgeX Foundry. There are starter guides and tutorials on the project page as well as docker-compose files on GitHub as per the below

Pulled images from Docker hub

Version 1.0.0 as far as the eye can see 🙂