Sound Integration

The Training Village uses the Raspberry DAC Pro HAT for audio output. Connect it directly on top of the Raspberry Pi or on top of the Main HAT if one is installed. Audio playback from within tasks is handled by the Python pyalsaaudio library, which talks to ALSA directly, without going through PortAudio.

Configuration

  1. Connect headphones or speakers to the DAC output.

  2. Right-click the volume icon in the top system bar and select Device Profiles. The RPi DAC Pro entry should appear in the list. Select it and set the output profile to Stereo Output.

  3. Play any audio to verify the DAC is working correctly.

  4. Once confirmed, return to Device Profiles, select RPi DAC Pro again, and set the profile to Off. The operating system will no longer use the device, leaving it free for pyalsaaudio to access directly.

Why the DAC must be released from the system before use

When the DAC is set as the active audio output in the desktop environment, the operating system holds exclusive access to the device, preventing the Training Village from using it. Setting the profile to Off releases the device and makes it available for the Training Village.

  1. Launch the Training Village and select your soundcard under SETTINGS → SOUND SETTINGS.

Note

This configuration step only needs to be done once. The “Off” profile selection persists across reboots, so the DAC will remain available to the Training Village after the system restarts.

Using the sound device in tasks

Audio files are read from the project’s media directory: /village_projects/<project_name>/media. This path is configured in SETTINGS → DIRECTORY SETTINGS as MEDIA_DIRECTORY. Place WAV files there and reference them by filename only (no path needed).

Every sound must be loaded before it is played — never call play twice in a row without a load in between. stop is optional, only needed to cut a sound short before it finishes on its own.

  1. load — decodes the audio and stages it in the buffer. This can be a slow operation (hundreds of ms depending on audio length), so it is best called during the inter-trial interval.

  2. play — starts playback of whatever is currently in the buffer. This is much faster — measured latencies are below 5 ms. Calling play again while a sound is still playing is ignored, so it must always be preceded by its own load.

  3. stop (optional) — interrupts playback mid-sound.

After calling stop, the buffer is no longer valid and a new load is required before the next play.

Fade-in / fade-out ramp

If the SOUND_RAMP_MS setting (SETTINGS → SOUND SETTINGS) is set to a value other than zero, a raised-cosine ramp of that duration is applied automatically to every sound: at its start, at its end, and whenever stop cuts playback short. This smooths out the abrupt amplitude changes that would otherwise cause audible clicks. Setting it to 0 disables the ramp entirely.

from village.devices.sound_device import sound_device

# Option 1 — play a WAV file from the media directory
gain = 0.5   # volume, from 0.0 (silent) to 1.0 (full scale)
left, right = sound_device.get_sound_from_wav("tone.wav", gain)
sound_device.load(left, right)
sound_device.play()

# To play the same sound again, load must be called again
left, right = sound_device.get_sound_from_wav("tone.wav", gain)
sound_device.load(left, right)
sound_device.play()

# Option 2 — generate a tone with numpy and play it
import numpy as np

samplerate = 192000          # must match SAMPLERATE setting
duration   = 0.5             # seconds
frequency  = 4000            # Hz

# volume calibrated so the tone measures 70 dB from speaker 1
gain = self.calibrations.sound_calibration.get_sound_gain(
    speaker=1, dB=70.0, sound_name="tone"
)

t = np.linspace(0, duration, int(samplerate * duration), endpoint=False)
tone = (gain * np.sin(2 * np.pi * frequency * t)).astype(np.float32)

sound_device.load(tone, tone)   # identical left and right channels → mono
sound_device.play()

get_sound_from_wav resamples the audio if the WAV’s sample rate does not match SAMPLERATE, and returns both channels as float32 arrays in the range [-1.0, 1.0], scaled by gain.

Prefer a matching sample rate

Resampling is a fallback, not something to rely on. It costs extra time on every get_sound_from_wav call and can degrade audio quality. Whenever possible, save your WAV files at the same sample rate as the SAMPLERATE setting so no resampling is needed.

Method reference

Method

Arguments

Description

get_sound_from_wav(file, gain)

file: filename, gain: volume, 0.0–1.0

Reads a WAV from MEDIA_DIRECTORY, applies gain, returns (left, right) arrays.

load(left, right)

numpy arrays, equal length

Stages stereo audio for playback. Pass None for a silent channel.

play()

—

Triggers playback of the loaded sound.

stop()

—

Interrupts playback.