Communication applications offer a better experience by enabling noise suppression as it helps listeners focus on the speaker. It elevates human-to-human communications in virtual settings whether it's a business call, customer service inquiry, online game, or family union. However, finding the best noise suppression software that runs in real time is not easy.
We gathered five major criteria to consider before choosing noise suppression software.
- Latency
- Platform Support
- Runtime
- Quality
- Cost
1. Latency
For streaming, latency should be minimal, and the only reliable way to guarantee that is to process voice data on the device. When latency creeps in, the sense of presence breaks and people start talking over each other. For non-streaming applications, this is not important. However, for streaming applications, it's a must.
2. Platform Support
Platform support is important for both streaming and non-streaming applications. It's important to make sure that the noise suppression software you're considering support all the platforms that your application currently runs and will run in the future. If it's a web-based meeting application, users will expect the same experience on every device and browser they use whether it's Chrome, Safari, or mobile Firefox.
3. Runtime
Noise Suppression software may be small and efficient enough to run on-device. However, it shouldn't impact the overall performance of your application or the device. If Noise Suppression software drains the battery of mobile devices due to high power requirements, then users will not be happy with your application.
4. Quality
After finding noise suppression software alternatives that are fast, efficient, and compatible with your application, then evaluate the quality. If the software doesn't perform well, then it won't add so much value to your application. Some engines do not perform well against short and loud non-stationary noises, such as sirens, and keyboard typing. Make sure your evaluation data set includes them as well if they matter. You can also use the open-source noise suppression benchmark developed by the Picovoice team. While working on Koala Noise Suppression, we noted that there was no scientific and transparent framework available to compare alternatives.
5. Cost
When there is free and open-source noise suppression software for streaming, RNNoise, why should you pay, right? Whether to buy, open-source or build is a famous debate in software development. It depends on many factors. Thus, the concept of the total cost of ownership is equally famous. Consider whether you have the in-house expertise to build and maintain, the types of noises you want to remove, how important the feature, hence support is, and the platforms you currently need and may need in the future.
Noise suppression software compared
| Software | Type | Real-time | Platforms | Developer integration |
|---|---|---|---|---|
| Krisp | End-user app, enterprise SDK program | Yes | Desktop, mobile | Yes |
| NVIDIA RTX Voice / Broadcast | End-user app | Yes | Windows with NVIDIA GPU | No |
| Apple Voice Isolation | OS feature | Yes | Apple devices | No |
| RNNoise | Open-source library | Yes | Cross-platform, self-built | Yes, self-maintained |
| Koala Noise Suppression | Developer SDK | Yes | Linux, macOS, Windows, Android, iOS, web, Raspberry Pi | Yes |
End-user tools such as Krisp, NVIDIA RTX Voice, and Apple Voice Isolation clean audio only for users who install and enable them, on hardware they support. For a streaming product, that leaves audio quality up to each viewer's setup. A developer SDK embeds noise suppression in the application itself, giving enterprises control over the user experience by offering every user the same clean audio. In Picovoice's open-source noise suppression benchmark, Koala reduces the STOI distance to clean speech to 0.0415 versus 0.0748 for RNNoise (lower is better) while running in real time. Krisp and the NVIDIA tools are not part of the benchmark set, so this page makes no head-to-head accuracy claim about them.
Noise reduction software vs noise suppression software
The two terms describe the same category. Noise reduction software is the broader audio-production term and includes offline clean-up tools for recorded audio. Noise suppression software usually implies real-time processing of live voice, which is what streaming needs. If a tool only works in post-production, it is not fit for a live stream, no matter how good the noise reduction is.
In similar articles, choosing the best natural language understanding and speech-to-text engines we concluded that there was not a single “best” engine for everyone, but the best engine for uses cases, applications, and different requirements. However, if you're looking for high-quality noise suppression software for streaming to build a commercial application, then this time there is the single best engine: Koala Noise Suppression. Do not just take our word, test out Koala Noise Suppression for free.
Want a runnable example? The real-time microphone noise removal recipe runs Koala Noise Suppression on a live microphone.
Frequently Asked Questions
For a streaming application you ship to users, a developer SDK beats an end-user tool, because the cleanup runs inside your product for everyone. In Picovoice's open-source noise suppression benchmark, Koala Noise Suppression scores a 0.0415 STOI distance to clean speech versus 0.0748 for RNNoise (lower is better) and runs in real time across desktop, mobile, and web.
Yes, it depends on the solution. Koala runs inside the browser via its Web SDK, so audio is processed locally on the viewer's machine without a server round trip. End-user desktop tools such as NVIDIA RTX Voice do not run inside your web app.
Krisp is primarily an end-user application, with SDK access through an enterprise program. Koala is a developer SDK first: you embed it in your application through self-service, and it runs on-device across Linux, macOS, Windows, Android, iOS, web, and Raspberry Pi. Picovoice's benchmark is open-source and reproducible, since Krisp SDK access is not available to every developer before a contract, it's not included in the benchmark to provide the head-to-head accuracy numbers.
RNNoise is free, open-source, and runs in real time, which makes it a reasonable baseline. In Picovoice's open-source benchmark, its STOI distance to clean speech is 0.0748 versus 0.0415 for Koala (lower is better), and as a community project it ships without support or maintenance guarantees. Whether that trade-off is acceptable depends on how central audio quality is to your product.
