How to Avoid Echo Cancellation Issues in Desktop Recording Apps

Recording audio in a desktop app sounds relatively straightforward: capture the user's microphone, capture the meeting audio, combine the two streams, and save the result.

In practice, one of the first problems you're likely to encounter is echo.

If someone joins a Zoom, Google Meet, or Microsoft Teams call without headphones, the remote participants' voices play through their computer speakers. The microphone then picks up some of that audio and records it again. When you combine the microphone track with the meeting audio, the same speech appears twice.

For a human listener, this creates an annoying echo. For a transcription or AI product, the consequences can be worse: duplicate words, incorrect speaker attribution, reduced transcription accuracy, and confusing downstream data.

Avoiding these problems requires more than simply capturing the right audio streams – you also need a reliable acoustic echo cancellation system.

In this article, we'll explain how acoustic echo cancellation works, why it's difficult to implement reliably in desktop recording apps, and how you can avoid building this infrastructure yourself with Recall.ai's Desktop Recording SDK.

What causes echo in a desktop recording app?

Imagine a user is on a video call with their laptop speakers enabled.

Your desktop recorder captures two sources:

Meeting audio, which contains the voices of the remote participants.
Microphone audio, which contains the local participant's voice.

The problem is that the microphone doesn't hear only the local participant. It can also hear audio being played through the laptop speakers.

If a remote participant says:

"Let's review the numbers from last quarter."

Your app may capture that sentence directly from the meeting application. A few milliseconds later, the microphone may capture the same sentence after it travels from the laptop speakers through the room and back into the microphone.

When the streams are combined, you now have two copies of the same speech.

This is the problem acoustic echo cancellation, or AEC, is designed to solve.

Microsoft describes AEC as audio processing that removes echo already present in an audio stream, while Apple provides voice-processing functionality specifically designed to remove device output from captured microphone audio.

How does acoustic echo cancellation work?

At a high level, an AEC system needs to understand what audio the computer is playing and compare that against what the microphone hears.

The audio being played through the speakers is commonly called the far-end reference signal.

The microphone signal contains a combination of:

the local speaker's voice
background noise
the far-end audio leaking through the speakers
room reflections and reverberation

The echo canceller attempts to identify the portion of the microphone signal that originated from the computer's speakers and remove it while preserving the local speaker.

Conceptually:

Microphone signal − estimated speaker echo = clean microphone audio

The difficult part is producing an accurate estimate.

Audio changes as it moves through a physical environment. Speaker characteristics, microphone position, volume, room acoustics, device latency, and even the location of the laptop can affect what the microphone receives.

The AEC algorithm therefore has to continuously model the acoustic path between the speaker and microphone.

Why echo cancellation is harder than it looks

You can add an AEC library to a desktop recorder, but the algorithm itself is only one part of the solution. A production-ready recorder also has to provide the algorithm with the right audio streams, keep them aligned, and handle changes in the user's audio environment.

1. Your audio streams need to stay synchronized

Your microphone and meeting audio may come from completely different APIs.

For example, a macOS application might capture microphone audio through one API and application or system audio through another. Those streams can have different:

sample rates
buffer sizes
timestamps
clock sources
processing delays

Poor or changing synchronization between these streams makes echo cancellation significantly harder.

The AEC system needs to align the far-end reference signal with the copy of that same audio arriving through the microphone. If the streams are incorrectly aligned, the algorithm can struggle to model the echo path, leaving residual echo or reducing cancellation effectiveness.

This becomes especially difficult during long recordings, where independently captured streams can gradually drift apart.

2. Operating systems handle audio processing differently

There isn't one universal desktop API you can enable to make echo disappear everywhere.

Apple provides voice-processing APIs that include acoustic echo cancellation. For example, applications using AVAudioEngine can enable voice processing on its I/O nodes with setVoiceProcessingEnabled(). Apple's voice-processing system is designed for applications such as VoIP and includes functionality such as echo cancellation.

Windows also supports acoustic echo cancellation through its audio-processing architecture, including AEC Audio Processing Objects. However, the available processing can depend on the audio device, driver, endpoint, and processing mode.

Having AEC capabilities available at the operating-system level therefore doesn't automatically solve the problem for a cross-platform recording application.

You still need to understand how those capabilities interact with:

your capture method
the selected input and output devices
different OS versions
different hardware
the meeting application
the rest of your audio-processing pipeline

If you're supporting both Windows and macOS, you're effectively maintaining different audio implementations and behavior across the two platforms.

3. Double-talk makes cancellation harder

A particularly difficult case occurs when the local and remote participants speak at the same time.

The microphone now contains both legitimate local speech and an acoustic copy of the remote speaker's audio. The echo canceller has to distinguish between the two without damaging the local speaker's voice.

If double-talk isn't handled correctly, the echo canceller can misestimate the echo path, while overly aggressive residual-echo suppression can attenuate parts of the local speaker's speech along with the echo.

That can make the recording sound unnatural to a human and can also result in missing words or degraded accuracy when the audio is sent to a transcription model.

4. You need to test real-world environments

A solution that works on one developer's MacBook in a quiet room isn't necessarily production ready.

Your users may have:

older laptops
inexpensive microphones
loud external speakers
docking stations
Bluetooth devices
unusual sample rates
virtual audio devices
outdated operating systems

Different rooms and speaker configurations also create different acoustic echo paths, which means an AEC system has to work across a wide range of real-world conditions.

Reliable meeting recording therefore means testing the complete audio pipeline across many hardware, software, and device configurations—not just getting echo cancellation working once.

Why headphones aren't a solution

The easiest way to prevent acoustic echo is to use headphones. When meeting audio doesn't play through speakers, very little of it reaches the microphone.

However, a recording application obviously can't assume users will always wear them. Requiring headphones introduces a significant constraint on the product experience, and is unrealistic to expect from your customers. For a production desktop recorder, echo cancellation therefore needs to work automatically.

Some approaches to handling echo cancellation

If you're building a desktop recording app, there are several approaches you can take.

Approach	Advantage	Main limitation
Require headphones	Almost eliminates speaker-to-mic echo	You can't guarantee users will wear headphones
Capture only output audio	Avoids acoustic echo	Doesn't capture the local speaker
Use native OS voice processing	Gives you access to built-in AEC capabilities	Requires OS-specific implementations and integration work
Add an AEC library	Gives you direct control over processing	You must capture, synchronize, tune, and maintain the audio pipeline

For prototypes, building your own audio pipeline may be reasonable.

The calculus changes when you need the recorder to work reliably across thousands of users and different combinations of operating systems, devices, browsers, meeting platforms, and audio configurations.

Avoid building the audio stack with Recall.ai's Desktop Recording SDK

The simplest way to avoid audio processing problems is to use a recording SDK that already handles them.

Recall.ai's Desktop Recording SDK provides production-ready audio capture for desktop meeting recorders, including built-in acoustic echo cancellation. It captures outgoing application audio and microphone audio while handling stream synchronization, mute detection, and other processing needed to produce usable meeting data.

Instead of building and maintaining separate capture pipelines with ScreenCaptureKit, CoreAudioTaps, AVFoundation, Electron APIs, and Windows audio APIs, you can integrate a single SDK built specifically for meeting recording.

Recall.ai supports desktop recording on macOS and Windows and can capture meetings from platforms like Zoom, Google Meet, and Microsoft Teams, in addition to other recording scenarios.

The best way to avoid echo cancellation issues

Building your own AEC stack can make sense for specialized audio applications. But for a meeting recorder, echo cancellation is just one of many infrastructure problems you'll need to solve.

Recall.ai's Desktop Recording SDK handles acoustic echo cancellation, microphone and meeting-audio capture, synchronization, mute detection, and other recording edge cases for you. That lets your engineering team focus on the features users actually care about instead of debugging audio pipelines across devices and operating systems.

If you need reliable, high-quality audio for a desktop meeting recorder, start with the Recall.ai Desktop Recording SDK.